Mercurial > pylearn
annotate nnet_ops.py @ 461:1243716ade6a
Rearranged
author | Joseph Turian <turian@iro.umontreal.ca> |
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date | Wed, 08 Oct 2008 01:09:23 -0400 |
parents | 34acf8db186d |
children | 2bef0768bc27 |
rev | line source |
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419
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added other_ops.py to nnet_ops; added basic tests, no docs.
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1 |
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2 import sys |
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3 sys.stderr.write("Use theano.sandbox.nnet_ops instead of pylearn.nnet_ops.\n") |
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4 if 0: |
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5 ## This file contain ops that are not currently integrated in the core of threano. |
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6 ## Not all of those ops have been thoroughly tested. |
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7 |
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8 import theano |
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9 from theano import tensor, scalar |
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10 import numpy |
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11 |
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12 ############ |
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13 # |
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14 # SCALAR OPS |
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15 # |
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16 |
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17 class ScalarSigmoid(scalar.UnaryScalarOp): |
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18 @staticmethod |
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19 def st_impl(x): |
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20 if x < -30.0: |
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21 return 0.0 |
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22 if x > 30.0: |
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23 return 1.0 |
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24 return 1.0 / (1.0 + numpy.exp(-x)) |
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25 def impl(self, x): |
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26 return ScalarSigmoid.st_impl(x) |
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27 def grad(self, (x,), (gz,)): |
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28 y = scalar_sigmoid(x) |
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29 return [gz * y * (1.0 - y)] |
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30 def c_code(self, node, name, (x,), (z,), sub): |
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31 if node.inputs[0].type in [scalar.float32, scalar.float64]: |
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32 return """%(z)s = |
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33 %(x)s < -30.0 |
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34 ? 0.0 |
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35 : %(x)s > 30.0 |
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36 ? 1.0 |
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37 : 1.0 /(1.0+exp(-%(x)s));""" % locals() |
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38 raise NotImplementedError('only floatingpoint is implemented') |
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39 scalar_sigmoid = ScalarSigmoid(scalar.upgrade_to_float, name='scalar_sigmoid') |
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40 sigmoid = tensor.Elemwise(scalar_sigmoid, name='sigmoid') |
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41 |
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42 class ScalarSoftplus(scalar.UnaryScalarOp): |
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43 @staticmethod |
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44 def static_impl(x): |
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45 if x < -30.0: |
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46 return 0.0 |
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47 if x > 30.0: |
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48 return x |
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49 return numpy.log1p(numpy.exp(x)) |
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50 def impl(self, x): |
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51 return ScalarSoftplus.static_impl(x) |
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52 def grad(self, (x,), (gz,)): |
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53 return [gz * scalar_sigmoid(x)] |
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54 def c_code(self, node, name, (x,), (z,), sub): |
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55 if node.inputs[0].type in [scalar.float32, scalar.float64]: |
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56 return """%(z)s = |
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57 %(x)s < -30.0 |
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58 ? 0.0 |
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59 : %(x)s > 30.0 |
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60 ? %(x)s |
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61 : log1p(exp(%(x)s));""" % locals() |
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62 raise NotImplementedError('only floating point x is implemented') |
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63 scalar_softplus = ScalarSoftplus(scalar.upgrade_to_float, name='scalar_softplus') |
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64 softplus = tensor.Elemwise(scalar_softplus, name='softplus') |
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65 |
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66 |
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67 ############ |
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68 # |
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69 # TENSOR OPS |
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70 # |
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71 |
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72 |
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73 class SoftmaxWithBias(theano.Op): |
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74 """ |
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75 An L{Op} for the output of neural-net multiclass classifiers. |
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76 |
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77 @type x: is a matrix of floats (32 or 64) |
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78 @type b: is a [row] vector of floats (32 or 64), length is number of cols in x |
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79 |
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80 This L{Op}'s output is softmax(x+b). |
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81 softmax(x[i]) is the i'th distribution over len(x[i]) options. |
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82 """ |
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83 |
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84 nin = 2 |
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85 nout = 1 |
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86 def __init__(self, **kwargs): |
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87 theano.Op.__init__(self, **kwargs) |
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88 |
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89 def make_node(self, x, b): |
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90 x = tensor.as_tensor(x) |
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91 b = tensor.as_tensor(b) |
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92 if x.type.ndim != 2 \ |
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93 or x.type.dtype not in ['float32', 'float64']: |
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94 raise ValueError('x must be 2-d tensor of floats') |
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95 if b.type.ndim != 1 \ |
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96 or x.type.dtype not in ['float32', 'float64']: |
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97 raise ValueError('b must be 1-d tensor of floats') |
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98 |
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99 sm = x.type.make_result() |
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100 return theano.Apply(self, [x, b], [sm]) |
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101 |
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102 def perform(self, node, input_storage, output_storage): |
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103 x, b = input_storage |
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104 if b.shape[0] != x.shape[1]: |
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105 raise ValueError('b must have same number of columns as x') |
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106 |
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107 sm = numpy.zeros_like(x) |
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108 for i in xrange(sm.shape[0]): |
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109 row = x[i] + b |
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110 sm[i] = numpy.exp(row - numpy.max(row)) |
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111 sm[i] *= 1.0 / numpy.sum(sm[i]) |
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112 output_storage[0][0] = sm |
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113 |
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114 def grad(self, (x, b), (g_sm,)): |
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115 sm = softmax_with_bias(x, b) |
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116 dx = SoftmaxWithBiasDx()(g_sm, sm) |
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117 db = tensor.sum(dx, axis = 0) |
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118 return dx, db |
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119 |
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120 def c_headers(self): |
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121 return ['<iostream>'] |
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122 |
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123 @staticmethod |
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124 def c_code_template(): |
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125 # this implementation was lifted from |
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126 # /u/bergstrj/cvs/bergstrj/src/feb07/nn.cxx |
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127 |
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128 #TODO: put this into a templated function, in the support code |
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129 #TODO: declare the max of each row as an Op output |
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130 |
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131 #TODO: set error messages for failures in this code |
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132 |
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133 #TODO: use this to accept float32 and int32: node.inputs[0].type.dtype_specs()[1] |
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134 init_decl = """ |
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135 npy_intp* Nx = %(x)s->dimensions; |
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136 |
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137 if (%(x)s->nd != 2) |
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138 { |
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139 PyErr_SetString(PyExc_ValueError, "a not 2d tensor"); |
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140 %(fail)s; |
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141 } |
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142 if (%(b)s->nd != 1) |
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143 { |
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144 PyErr_SetString(PyExc_ValueError, "b not 1d tensor"); |
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145 %(fail)s; |
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146 } |
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147 if (%(x)s->descr->type_num != PyArray_DOUBLE) |
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148 { |
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149 PyErr_SetString(PyExc_TypeError, "a not float64"); |
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150 %(fail)s; |
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151 } |
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152 if (%(b)s->descr->type_num != PyArray_DOUBLE) |
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153 { |
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154 PyErr_SetString(PyExc_TypeError, "b not float64"); |
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155 %(fail)s; |
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156 } |
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157 if ((%(x)s->dimensions[1] != %(b)s->dimensions[0])) |
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158 { |
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159 PyErr_SetString(PyExc_ValueError, "dimension mismatch in arguments"); |
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160 %(fail)s; |
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161 } |
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162 |
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163 if ((NULL == %(sm)s) |
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164 || (%(sm)s->dimensions[0] != %(x)s->dimensions[0]) |
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165 || (%(sm)s->dimensions[1] != %(x)s->dimensions[1])) |
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166 { |
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167 if (NULL != %(sm)s) Py_XDECREF(%(sm)s); |
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168 %(sm)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(x)s), type_num_%(x)s); |
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169 if(!%(sm)s) { |
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170 PyErr_SetString(PyExc_MemoryError, "failed to alloc sm output"); |
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171 %(fail)s |
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172 } |
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173 } |
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174 """ |
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175 |
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176 begin_row_loop = """ |
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177 for (size_t i = 0; i < Nx[0]; ++i) |
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178 { |
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179 size_t j; |
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180 double sum = 0.0; |
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181 bool discount_max = false; |
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182 |
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183 const double* __restrict__ x_i = (double*)(%(x)s->data + %(x)s->strides[0] * i); |
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184 const double* __restrict__ b_i = (double*)(%(b)s->data); |
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185 double* __restrict__ sm_i = (double*)(%(sm)s->data + %(sm)s->strides[0] * i); |
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186 """ |
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187 |
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188 inside_row_loop = """ |
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189 npy_intp Sx = %(x)s->strides[1]/sizeof(double); |
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190 npy_intp Sb = %(b)s->strides[0]/sizeof(double); |
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191 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double); |
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192 |
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193 size_t row_max_j=0; |
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194 double row_max = x_i[0] + b_i[0]; |
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195 // Get the maximum value of the row |
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196 for (j = 0; j < Nx[1]; ++j) |
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197 { |
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198 double row_ij = x_i[j * Sx] + b_i[j * Sb]; |
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199 row_max_j = (row_ij > row_max) ? j : row_max_j; |
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200 row_max = (row_ij > row_max) ? row_ij : row_max; |
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201 } |
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202 |
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203 for (j = 0; j < Nx[1]; ++j) |
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204 { |
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205 double row_ij = x_i[j * Sx] + b_i[j * Sb]; |
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206 double sm_ij = exp(row_ij - row_max); |
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207 sum += sm_ij; |
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208 sm_i[j * Ssm] = sm_ij; |
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209 } |
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210 if ( (0.0 == sum) || (isinf(sum))) |
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211 { |
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212 //that was our best... |
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213 %(fail)s; |
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214 } |
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215 |
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216 //cblas_dscal(x.N, 1.0 / sum, &mat_at(s,i,0), s.n); |
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217 double sum_inv = 1.0 / sum; |
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218 for (j = 0; j < Nx[1]; ++j) |
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219 { |
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220 sm_i[j * Ssm] *= sum_inv; |
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221 } |
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222 |
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223 """ |
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224 |
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225 end_row_loop = """ |
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226 } |
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227 """ |
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228 |
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229 return (init_decl, begin_row_loop, inside_row_loop, end_row_loop) |
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230 |
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231 |
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232 def c_code(self, node, name, (x, b), (sm,), sub): |
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233 code_template = ''.join(self.c_code_template()) |
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234 return code_template % dict(locals(), **sub) |
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235 |
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236 softmax_with_bias = SoftmaxWithBias() |
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237 |
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238 |
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239 class SoftmaxWithBiasDx(theano.Op): |
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240 nin = 2 |
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241 nout = 1 |
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242 """Gradient wrt x of the SoftmaxWithBias Op""" |
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243 |
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244 def __init__(self, **kwargs): |
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245 theano.Op.__init__(self, **kwargs) |
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246 |
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247 def make_node(self, dy, sm, **kwargs): |
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248 dy = tensor.as_tensor(dy) |
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249 sm = tensor.as_tensor(sm) |
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250 return theano.Apply(self, [dy, sm], [sm.type.make_result()]) |
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251 |
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252 def perform(self, node, input_storage, output_storage): |
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253 dy, sm = input_storage |
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254 dx = numpy.zeros_like(sm) |
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255 #dx[i,j] = - (\sum_k dy[i,k] sm[i,k]) sm[i,j] + dy[i,j] sm[i,j] |
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256 for i in xrange(sm.shape[0]): |
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257 dy_times_sm_i = dy[i] * sm[i] |
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258 dx[i] = dy_times_sm_i - sum(dy_times_sm_i) * sm[i] |
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259 output_storage[0][0] = dx |
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260 |
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261 def grad(self, *args): |
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262 raise NotImplementedError() |
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263 |
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264 def c_code(self, node, name, (dy, sm), (dx,), sub): |
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265 return ''' |
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266 if ((%(dy)s->descr->type_num != PyArray_DOUBLE) |
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267 || (%(sm)s->descr->type_num != PyArray_DOUBLE)) |
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268 { |
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269 PyErr_SetString(PyExc_TypeError, "types should be float64, float64"); |
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270 %(fail)s; |
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271 } |
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272 if ((%(dy)s->nd != 2) |
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273 || (%(sm)s->nd != 2)) |
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274 { |
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275 PyErr_SetString(PyExc_ValueError, "rank error"); |
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276 %(fail)s; |
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277 } |
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278 if (%(dy)s->dimensions[0] != %(sm)s->dimensions[0]) |
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279 { |
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280 PyErr_SetString(PyExc_ValueError, "dimension mismatch"); |
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281 %(fail)s; |
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282 } |
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283 if ((NULL == %(dx)s) |
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284 || (%(dx)s->dimensions[0] != %(sm)s->dimensions[0]) |
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285 || (%(dx)s->dimensions[1] != %(sm)s->dimensions[1])) |
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286 { |
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287 Py_XDECREF(%(dx)s); |
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288 %(dx)s = (PyArrayObject*) PyArray_SimpleNew(2, PyArray_DIMS(%(sm)s), |
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289 type_num_%(sm)s); |
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290 if (!%(dx)s) |
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291 { |
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292 PyErr_SetString(PyExc_MemoryError, "failed to alloc dx output"); |
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293 %(fail)s; |
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294 } |
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295 } |
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296 |
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297 for (size_t i = 0; i < %(dx)s->dimensions[0]; ++i) |
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298 { |
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299 const double* __restrict__ dy_i = (double*) (%(dy)s->data + %(dy)s->strides[0] * i); |
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300 npy_intp Sdy = %(dy)s->strides[1]/sizeof(double); |
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301 const double* __restrict__ sm_i = (double*) (%(sm)s->data + %(sm)s->strides[0] * i); |
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302 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double); |
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303 double* __restrict__ dx_i = (double*) (%(dx)s->data + %(dx)s->strides[0] * i); |
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304 npy_intp Sdx = %(dx)s->strides[1]/sizeof(double); |
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305 |
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306 double sum_dy_times_sm = 0.; |
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307 for (size_t j = 0; j < %(dx)s->dimensions[1]; ++j) |
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308 { |
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309 dx_i[j * Sdx] = dy_i[j * Sdy] * sm_i[j * Ssm]; |
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310 sum_dy_times_sm += dx_i[j * Sdx]; |
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311 } |
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312 for (size_t j = 0; j < %(dx)s->dimensions[1]; ++j) |
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313 { |
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314 dx_i[j * Sdx] -= sum_dy_times_sm * sm_i[j * Ssm]; |
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315 } |
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316 } |
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317 ''' % dict(locals(), **sub) |
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318 |
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319 def softmax(x, **kwargs): |
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320 b = tensor.zeros_like(x[0,:]) |
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321 return softmax_with_bias(x, b, **kwargs) |
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322 |
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323 |
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324 class CrossentropySoftmaxArgmax1HotWithBias(theano.Op): |
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325 """A special compound L{Op} for the output of neural-net classifiers. |
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326 |
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327 @type x: is a matrix of floats (32 or 64) |
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328 @type b: is a [row] vector of floats (32 or 64), length is number of cols in x |
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329 @type y_idx: a [column] vector of int (32 or 64), length is number of rows in x |
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330 |
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331 @precondition: every entry in y_idx is a valid (non-negative) column index into x |
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332 |
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333 This L{Op} has three outputs: |
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334 - KL(softmax(x+b), y) |
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335 - softmax(x+b) |
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336 - argmax(x+b) |
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337 |
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338 softmax(x[i]) is the i'th distribution over len(x[i]) options |
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339 argmax(x) is the index of x's greatest element |
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340 y_idx[i] is an integer index, encoding a 1-hot distribution. |
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341 |
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342 In practice, when we're trying to do classification, we have one row in x |
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343 and y_idx per example, and y[i] is the index of the (correct) class of the |
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344 i'th example. |
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345 |
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346 """ |
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347 nin=3 |
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348 nout=3 |
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349 def __init__(self, **kwargs): |
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350 theano.Op.__init__(self, **kwargs) |
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351 |
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352 def make_node(self, x, b, y_idx): |
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353 x = tensor.as_tensor(x) |
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354 b = tensor.as_tensor(b) |
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Deprecated pylearn.nnet_ops.
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|
355 y_idx = tensor.as_tensor(y_idx) |
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Deprecated pylearn.nnet_ops.
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|
356 if x.type.ndim != 2 \ |
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Deprecated pylearn.nnet_ops.
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449
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|
357 or x.type.dtype not in ['float32', 'float64']: |
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Deprecated pylearn.nnet_ops.
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|
358 raise ValueError('x must be 2-d tensor of floats') |
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Deprecated pylearn.nnet_ops.
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|
359 if b.type.ndim != 1 \ |
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Deprecated pylearn.nnet_ops.
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360 or x.type.dtype not in ['float32', 'float64']: |
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Deprecated pylearn.nnet_ops.
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|
361 raise ValueError('b must be 1-d tensor of floats') |
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Deprecated pylearn.nnet_ops.
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|
362 if y_idx.type.ndim != 1 \ |
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Deprecated pylearn.nnet_ops.
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363 or y_idx.type.dtype not in ['int8', 'int16', 'int32', 'int64']: |
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Deprecated pylearn.nnet_ops.
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|
364 raise ValueError('y_idx must be 1-d tensor of ints') |
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Deprecated pylearn.nnet_ops.
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|
365 |
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366 # TODO: Is this correct? It used to be y, not y_idx |
34acf8db186d
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367 nll = tensor.Tensor(x.type.dtype, |
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Deprecated pylearn.nnet_ops.
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368 y_idx.type.broadcastable).make_result() |
34acf8db186d
Deprecated pylearn.nnet_ops.
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369 # nll = Tensor(x.dtype, y.broadcastable) |
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370 sm = x.type.make_result() |
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371 am = y_idx.type.make_result() |
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372 return theano.Apply(self, [x, b, y_idx], [nll, sm, am]) |
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Deprecated pylearn.nnet_ops.
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373 def perform(self, node, input_storage, output_storage): |
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Deprecated pylearn.nnet_ops.
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|
374 """ |
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|
375 The math, where x is an input vector, and t is a target index: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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|
376 |
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changeset
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377 softmax(x)[i] = exp(x[i]) / sum_j(exp(x[j])) |
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Deprecated pylearn.nnet_ops.
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|
378 nll(x,t) = -log(softmax(x)[t]) |
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Deprecated pylearn.nnet_ops.
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|
379 |
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|
380 We compute this by subtracting off the max of x. This avoids numerical instability. |
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|
381 |
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|
382 m = max_j x[j] |
34acf8db186d
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changeset
|
383 softmax(x)[i] = exp(x[i] -m) / sum_j(exp(x[j] - m)) |
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Deprecated pylearn.nnet_ops.
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changeset
|
384 |
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changeset
|
385 nll = -log(exp(x[t] -m) / sum_j(exp(x[j] - m))) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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changeset
|
386 = -x[t] + m + log( sum_j(exp(x[j] - m))) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
387 |
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Joseph Turian <turian@iro.umontreal.ca>
parents:
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diff
changeset
|
388 """ |
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|
389 x, b, y_idx = input_storage |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
390 if b.shape[0] != x.shape[1]: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
391 raise ValueError('b must have same number of columns as x') |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
392 if y_idx.shape[0] != x.shape[0]: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
393 raise ValueError('y_idx must have same number of rows as x') |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
394 |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
395 sm = numpy.zeros_like(x) # softmax |
34acf8db186d
Deprecated pylearn.nnet_ops.
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449
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changeset
|
396 nll = numpy.zeros(x.shape[0]) #nll(y | softmax(x)) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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449
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|
397 am = numpy.zeros_like(y_idx) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
398 for i in xrange(sm.shape[0]): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
399 #add the bias vector to the i'th row of x |
34acf8db186d
Deprecated pylearn.nnet_ops.
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449
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changeset
|
400 row = x[i] + b |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
401 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
402 #get the maximum value of i'th row for numerically safe softmax / nll |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
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changeset
|
403 am[i] = numpy.argmax(row) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
404 m = row[am[i]] |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
405 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
406 #compute the unnormalized softmax, and normalization constant |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
407 sm[i] = numpy.exp(row - m) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
408 sum_j = numpy.sum(sm[i]) # sum_j(exp(x[j] - m)) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
409 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
410 #normalized our softmax |
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Deprecated pylearn.nnet_ops.
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449
diff
changeset
|
411 sm[i] *= 1.0 / sum_j |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
412 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
413 # store the nll |
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parents:
449
diff
changeset
|
414 nll[i] = -row[y_idx[i]] + m + numpy.log(sum_j) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
415 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
416 output_storage[0][0] = nll |
34acf8db186d
Deprecated pylearn.nnet_ops.
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diff
changeset
|
417 output_storage[1][0] = sm |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
418 output_storage[2][0] = am |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
419 def grad(self, (x, b, y_idx), (g_nll, g_sm, g_am)): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
420 if g_sm is not None or g_am is not None: |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
421 raise NotImplementedError() |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
422 nll, sm = crossentropy_softmax_1hot_with_bias(x, b, y_idx) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
423 dx = CrossentropySoftmax1HotWithBiasDx()(g_nll, sm, y_idx) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
424 db = tensor.sum(dx, axis = [0]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
425 return dx, db, None |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
426 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
427 def c_headers(self): return ['<iostream>'] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
428 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
429 @staticmethod |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
430 def c_code_template(): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
431 # this implementation was lifted from |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
432 # /u/bergstrj/cvs/bergstrj/src/feb07/nn.cxx |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
433 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
434 #TODO: put this into a templated function, in the support code |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
435 #TODO: declare the max of each row as an Op output |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
436 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
437 #TODO: set error messages for failures in this code |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
438 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
439 #TODO: use this to accept float32 and int32: node.inputs[0].type.dtype_specs()[1] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
440 (init_decl, begin_row_loop, inside_row_loop, end_row_loop) = \ |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
441 SoftmaxWithBias.c_code_template() |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
442 return (init_decl, |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
443 """ |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
444 if (%(y_idx)s->nd != 1) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
445 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
446 PyErr_SetString(PyExc_ValueError, "y_idx not 1d tensor"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
447 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
448 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
449 if ((%(y_idx)s->descr->type_num != PyArray_INT64) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
450 && (%(y_idx)s->descr->type_num != PyArray_INT32) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
451 && (%(y_idx)s->descr->type_num != PyArray_INT16) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
452 && (%(y_idx)s->descr->type_num != PyArray_INT8)) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
453 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
454 PyErr_SetString(PyExc_TypeError, "y_idx not int8, int16, int32, or int64"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
455 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
456 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
457 if (%(x)s->dimensions[0] != %(y_idx)s->dimensions[0]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
458 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
459 PyErr_SetString(PyExc_ValueError, "dimension mismatch in arguments"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
460 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
461 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
462 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
463 if ((NULL == %(nll)s) //initial condition |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
464 || (%(nll)s->dimensions[0] != %(y_idx)s->dimensions[0])) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
465 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
466 if (NULL != %(nll)s) Py_XDECREF(%(nll)s); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
467 %(nll)s = (PyArrayObject*)PyArray_SimpleNew(1, PyArray_DIMS(%(y_idx)s), type_num_%(x)s); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
468 if(!%(nll)s) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
469 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
470 PyErr_SetString(PyExc_MemoryError, "failed to alloc nll output"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
471 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
472 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
473 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
474 if ((NULL == %(am)s) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
475 || (%(am)s->dimensions[0] != %(y_idx)s->dimensions[0])) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
476 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
477 Py_XDECREF(%(am)s); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
478 %(am)s = (PyArrayObject*) PyArray_SimpleNew(1, PyArray_DIMS(%(y_idx)s), type_num_%(y_idx)s); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
479 if(!%(am)s) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
480 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
481 PyErr_SetString(PyExc_MemoryError, "failed to alloc am output"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
482 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
483 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
484 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
485 """, |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
486 begin_row_loop, |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
487 """ |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
488 const %(y_idx_type)s y_i = ((%(y_idx_type)s*)(%(y_idx)s->data + %(y_idx)s->strides[0] * i))[0]; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
489 double* __restrict__ nll_i = (double*)(%(nll)s->data + %(nll)s->strides[0] * i); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
490 %(am_type)s* __restrict__ am_i = (%(am_type)s*) (%(am)s->data + %(am)s->strides[0] * i); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
491 """, |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
492 inside_row_loop, |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
493 """ |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
494 nll_i[0] = - x_i[y_i*Sx] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
495 - b_i[y_i*Sb] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
496 + row_max |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
497 + log(sum); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
498 am_i[0] = row_max_j; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
499 """, |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
500 end_row_loop) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
501 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
502 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
503 def c_code(self, node, name, (x, b, y_idx), (nll, sm, am), sub): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
504 y_idx_type = node.inputs[2].type.dtype_specs()[1] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
505 am_type = y_idx_type |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
506 code_template = ''.join(self.c_code_template()) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
507 return code_template % dict(locals(), **sub) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
508 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
509 class CrossentropySoftmax1HotWithBiasDx (theano.Op): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
510 nin=3 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
511 nout=1 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
512 """Gradient wrt x of the CrossentropySoftmax1Hot Op""" |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
513 def __init__(self, **kwargs): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
514 theano.Op.__init__(self,**kwargs) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
515 def make_node(self, dy, sm, y_idx,**kwargs): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
516 dy = tensor.as_tensor(dy) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
517 sm = tensor.as_tensor(sm) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
518 y_idx = tensor.as_tensor(y_idx) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
519 return theano.Apply(self, [dy, sm, y_idx],[sm.type.make_result()]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
520 def perform(self, node, input_storage, output_storage): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
521 dy,sm,y_idx = input_storage |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
522 dx = numpy.zeros_like(sm) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
523 for i in xrange(sm.shape[0]): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
524 dx[i] = dy[i] * sm[i] #vector scale |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
525 dx[i, y_idx[i]] -= dy[i] #scalar decrement |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
526 output_storage[0][0] = dx |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
527 def grad(self, *args): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
528 raise NotImplementedError() |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
529 def c_code(self, node, name, (dnll, sm, y_idx), (dx,), sub): |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
530 y_idx_type = node.inputs[2].type.dtype_specs()[1] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
531 return """ |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
532 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
533 if ((%(dnll)s->descr->type_num != PyArray_DOUBLE) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
534 || (%(sm)s->descr->type_num != PyArray_DOUBLE) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
535 ) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
536 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
537 PyErr_SetString(PyExc_TypeError, "types should be float64, float64, int64"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
538 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
539 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
540 if ((%(y_idx)s->descr->type_num != PyArray_INT64) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
541 && (%(y_idx)s->descr->type_num != PyArray_INT32) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
542 && (%(y_idx)s->descr->type_num != PyArray_INT16) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
543 && (%(y_idx)s->descr->type_num != PyArray_INT8)) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
544 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
545 PyErr_SetString(PyExc_TypeError, "y_idx not int8, int16, int32, or int64"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
546 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
547 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
548 if ((%(dnll)s->nd != 1) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
549 || (%(sm)s->nd != 2) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
550 || (%(y_idx)s->nd != 1)) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
551 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
552 PyErr_SetString(PyExc_ValueError, "rank error"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
553 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
554 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
555 if ((%(dnll)s->dimensions[0] != %(sm)s->dimensions[0]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
556 || (%(dnll)s->dimensions[0] != %(y_idx)s->dimensions[0])) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
557 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
558 PyErr_SetString(PyExc_ValueError, "dimension mismatch"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
559 %(fail)s; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
560 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
561 if ((NULL == %(dx)s) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
562 || (%(dx)s->dimensions[0] != %(sm)s->dimensions[0]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
563 || (%(dx)s->dimensions[1] != %(sm)s->dimensions[1])) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
564 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
565 if (NULL != %(dx)s) Py_XDECREF(%(dx)s); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
566 %(dx)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(sm)s), type_num_%(sm)s); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
567 if(!%(dx)s) { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
568 PyErr_SetString(PyExc_MemoryError, "failed to alloc dx output"); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
569 %(fail)s |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
570 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
571 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
572 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
573 for (size_t i = 0; i < %(dx)s->dimensions[0]; ++i) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
574 { |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
575 const double dnll_i = ((double*)(%(dnll)s->data + %(dnll)s->strides[0] * i))[0]; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
576 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
577 const %(y_idx_type)s y_i = ((%(y_idx_type)s*)(%(y_idx)s->data + %(y_idx)s->strides[0] * i))[0]; |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
578 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
579 const double* __restrict__ sm_i = (double*)(%(sm)s->data + %(sm)s->strides[0] * i); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
580 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double); |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
581 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
582 double* __restrict__ dx_i = (double*)(%(dx)s->data + %(dx)s->strides[0] * i); |
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Deprecated pylearn.nnet_ops.
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|
583 npy_intp Sdx = %(dx)s->strides[1]/sizeof(double); |
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Deprecated pylearn.nnet_ops.
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diff
changeset
|
584 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
585 for (size_t j = 0; j < %(dx)s->dimensions[1]; ++j) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
586 { |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
587 dx_i[j * Sdx] = dnll_i * sm_i[j * Ssm]; |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
588 } |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
589 if (y_i >= %(dx)s->dimensions[1]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
590 { |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
591 %(fail)s; |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
592 } |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
593 dx_i[y_i * Sdx] -= dnll_i; |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
594 } |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
595 """ % dict(locals(), **sub) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
596 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
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changeset
|
597 crossentropy_softmax_argmax_1hot_with_bias = \ |
34acf8db186d
Deprecated pylearn.nnet_ops.
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diff
changeset
|
598 CrossentropySoftmaxArgmax1HotWithBias() |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
599 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
600 def crossentropy_softmax_1hot_with_bias(x, b, y_idx, **kwargs): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
601 return crossentropy_softmax_argmax_1hot_with_bias(x, b, y_idx, **kwargs)[0:2] |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
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changeset
|
602 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
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diff
changeset
|
603 def crossentropy_softmax_1hot(x, y_idx, **kwargs): |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
604 b = tensor.zeros_like(x[0,:]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
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diff
changeset
|
605 return crossentropy_softmax_1hot_with_bias(x, b, y_idx, **kwargs) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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449
diff
changeset
|
606 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
607 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
608 class MultinomialCrossentropy1Hot(theano.Op): |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
609 pass |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
610 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
611 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
612 def binary_crossentropy(output, target): |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
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changeset
|
613 """ |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
614 Compute the crossentropy of binary output wrt binary target. |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
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changeset
|
615 @note: We do not sum, crossentropy is computed by component. |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
616 @todo: Rewrite as a scalar, and then broadcast to tensor. |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
617 @todo: This is essentially duplicated as cost.cross_entropy |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
618 @warning: OUTPUT and TARGET are reversed in cost.cross_entropy |
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Deprecated pylearn.nnet_ops.
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parents:
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changeset
|
619 """ |
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Deprecated pylearn.nnet_ops.
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changeset
|
620 return -(target * tensor.log(output) + (1 - target) * tensor.log(1 - output)) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
621 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
622 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
623 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
624 class Prepend_scalar_constant_to_each_row(theano.Op): |
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Deprecated pylearn.nnet_ops.
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parents:
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changeset
|
625 def __init__(self, val = 0): |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
626 if isinstance(val, float): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
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diff
changeset
|
627 val = scalar.constant(val) |
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Deprecated pylearn.nnet_ops.
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diff
changeset
|
628 self.val = val |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
629 |
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Deprecated pylearn.nnet_ops.
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parents:
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diff
changeset
|
630 def make_node(self, mat): |
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Deprecated pylearn.nnet_ops.
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449
diff
changeset
|
631 #check type of input |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
632 if not isinstance(mat,theano.Result) or not mat.type==tensor.matrix().type: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
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diff
changeset
|
633 raise TypeError("Expected a matrix as input") |
34acf8db186d
Deprecated pylearn.nnet_ops.
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diff
changeset
|
634 x = tensor.as_tensor(mat) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
635 y = tensor.as_tensor(self.val) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
636 if x.type.dtype != y.type.dtype: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
637 TypeError("the value to prepend don't have the same type as the matrix") |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
638 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
639 node = theano.Apply(op=self, inputs=[mat], outputs=[tensor.matrix()]) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
640 return node |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
641 |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
642 def perform(self, node, (mat, ), (output, )): |
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parents:
449
diff
changeset
|
643 new_shape=(mat.shape[0],mat.shape[1]+1) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
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changeset
|
644 if output[0] == None: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
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diff
changeset
|
645 output[0]=numpy.empty(new_shape,dtype=mat.dtype) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
646 out=output[0] |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
647 else: |
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parents:
449
diff
changeset
|
648 if output[0].shape!=new_shape: |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
649 try: |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
650 output[0].resize(new_shape) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
651 except: |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
652 output[0]=numpy.empty(new_shape, dtype=mat.dtype) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
653 out=output[0] |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
654 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
655 out[:,0].fill(self.val.data) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
656 out[:,1:]=mat |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
657 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
658 def grad(self, (mat,), (goutput,)): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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diff
changeset
|
659 return goutput[:,1:] |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
660 |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
661 class Prepend_scalar_to_each_row(theano.Op): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
662 def make_node(self, val, mat): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
663 #check type of input |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
664 if isinstance(val, float): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
665 val = scalar.constant(val) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
666 if not isinstance(mat,theano.Result) or not mat.type==tensor.matrix().type: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
667 raise TypeError("Expected a matrix as input") |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
668 x = tensor.as_tensor(mat) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
669 y = tensor.as_tensor(val) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
670 if x.type.dtype != y.type.dtype: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
671 TypeError("the value to prepend don't have the same type as the matrix") |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
672 |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
673 node = theano.Apply(op=self, inputs=[val,mat], outputs=[tensor.matrix()]) |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
674 return node |
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Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
675 |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
676 def perform(self, node, (val,mat), (output, )): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
677 new_shape=(mat.shape[0],mat.shape[1]+1) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
678 if output[0] == None: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
679 output[0]=numpy.empty(new_shape,dtype=mat.dtype) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
680 out=output[0] |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
681 else: |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
682 if output[0].shape!=new_shape: |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
683 try: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
684 output[0].resize(new_shape) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
685 except: |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
686 output[0]=numpy.empty(new_shape, dtype=mat.dtype) |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
687 out=output[0] |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
688 out[:,0].fill(val) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
689 out[:,1:]=mat |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
690 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
691 def grad(self, (val, mat), (goutput,)): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
692 return goutput[:,0], goutput[:,1:] |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
693 |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
694 prepend_scalar_to_each_row = Prepend_scalar_to_each_row() |
34acf8db186d
Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
695 prepend_0_to_each_row = Prepend_scalar_constant_to_each_row(0.) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
696 prepend_1_to_each_row = Prepend_scalar_constant_to_each_row(1.) |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
697 |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
698 class solve(theano.Op): |
34acf8db186d
Deprecated pylearn.nnet_ops.
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parents:
449
diff
changeset
|
699 """ |
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Deprecated pylearn.nnet_ops.
Joseph Turian <turian@iro.umontreal.ca>
parents:
449
diff
changeset
|
700 Find the solution to the linear equation Ax=b, |
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parents:
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701 where A is a 2d matrix and b is a 1d or 2d matrix. |
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parents:
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702 It use numpy.solve to find the solution. |
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parents:
449
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703 """ |
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parents:
449
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704 |
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Deprecated pylearn.nnet_ops.
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parents:
449
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705 def make_node(self, A, b): |
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parents:
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706 if not isinstance(A, theano.Result) or not A.type==tensor.matrix().type: |
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parents:
449
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707 raise TypeError("We expected that A had a matrix type") |
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parents:
449
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708 if not isinstance(B, theano.Result) or not B.type==tensor.matrix().type: |
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parents:
449
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709 raise TypeError("We expected that B had a matrix type") |
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parents:
449
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710 |
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parents:
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711 node = theano.Apply(op=self, inputs=[A, B], outputs=[tensor.matrix()]) |
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parents:
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712 return node |
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Joseph Turian <turian@iro.umontreal.ca>
parents:
449
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713 |
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parents:
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714 def perform(self, node, (A, B), (output, )): |
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parents:
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715 ret=numpy.solve(A,B) |
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parents:
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716 output[0]=ret |
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parents:
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717 |
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parents:
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718 def grad(self, (theta, A, B), (gtheta,)): |
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parents:
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719 raise NotImplementedError() |
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parents:
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720 |
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parents:
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721 |