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annotate nnet_ops.py @ 422:32c5f87bc54e

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Added __len__ to HStackedDataSet and replaced default len() by sys.maxint instead of None
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Sat, 19 Jul 2008 14:12:41 -0400
parents 43d9aa93934e
children 18dbc1c11647
rev   line source
419
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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1 ## This file contain ops that are not currently integrated in the core of threano.
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2 ## Not all of those ops have been thoroughly tested.
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3
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4 import theano
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5 from theano import tensor, scalar
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6 import numpy
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7
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8 ############
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9 #
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10 # SCALAR OPS
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11 #
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12
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13 class ScalarSigmoid(scalar.UnaryScalarOp):
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14 @staticmethod
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15 def st_impl(x):
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16 if x < -30.0:
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17 return 0.0
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18 if x > 30.0:
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19 return 1.0
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20 return 1.0 / (1.0 + numpy.exp(-x))
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21 def impl(self, x):
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22 return ScalarSigmoid.st_impl(x)
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23 def grad(self, (x,), (gz,)):
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24 y = scalar_sigmoid(x)
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25 return [gz * y * (1.0 - y)]
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26 def c_code(self, node, name, (x,), (z,), sub):
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27 if node.inputs[0].type in [scalar.float32, scalar.float64]:
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28 return """%(z)s =
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29 %(x)s < -30.0
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30 ? 0.0
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31 : %(x)s > 30.0
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32 ? 1.0
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33 : 1.0 /(1.0+exp(-%(x)s));""" % locals()
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34 raise NotImplementedError('only floatingpoint is implemented')
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35 scalar_sigmoid = ScalarSigmoid(scalar.upgrade_to_float, name='scalar_sigmoid')
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36 sigmoid = tensor.Elemwise(scalar_sigmoid, name='sigmoid')
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37
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38 class ScalarSoftplus(scalar.UnaryScalarOp):
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39 @staticmethod
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40 def static_impl(x):
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41 if x < -30.0:
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42 return 0.0
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43 if x > 30.0:
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44 return x
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45 return numpy.log1p(numpy.exp(x))
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46 def impl(self, x):
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47 return ScalarSoftplus.static_impl(x)
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48 def grad(self, (x,), (gz,)):
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49 return [gz * scalar_sigmoid(x)]
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50 def c_code(self, node, name, (x,), (z,), sub):
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51 if node.inputs[0].type in [scalar.float32, scalar.float64]:
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52 return """%(z)s =
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53 %(x)s < -30.0
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54 ? 0.0
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55 : %(x)s > 30.0
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56 ? %(x)s
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57 : log1p(exp(%(x)s));""" % locals()
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58 raise NotImplementedError('only floating point x is implemented')
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59 scalar_softplus = ScalarSoftplus(scalar.upgrade_to_float, name='scalar_softplus')
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60 softplus = tensor.Elemwise(scalar_softplus, name='softplus')
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63 ############
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64 #
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65 # TENSOR OPS
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66 #
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67
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68 class CrossentropySoftmax1HotWithBias(theano.Op):
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69 """A special compound L{Op} for the output of neural-net classifiers.
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70
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71 @type x: is a matrix of floats (32 or 64)
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72 @type b: is a [row] vector of floats (32 or 64), length is number of cols in x
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73 @type y_idx: a [column] vector of int (32 or 64), length is number of rows in x
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74
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75 @precondition: every entry in y_idx is a valid (non-negative) column index into x
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76
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77 This L{Op} has two outputs:
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78 - KL(softmax(x+b), y)
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79 - softmax(x+b)
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80
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81
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82 softmax(x[i]) is the i'th distribution over len(x[i]) options
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83
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84 y_idx[i] is an integer index, encoding a 1-hot distribution.
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85
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86 In practice, when we're trying to do classification, we have one row in x
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87 and y_idx per example, and y[i] is the index of the (correct) class of the
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88 i'th example.
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89
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90 """
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91 nin=3
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92 nout=2
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93 def __init__(self, **kwargs):
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94 theano.Op.__init__(self, **kwargs)
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95
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96 def make_node(self, x, b, y_idx):
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97 x = tensor.as_tensor(x)
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98 b = tensor.as_tensor(b)
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99 y_idx = tensor.as_tensor(y_idx)
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100 if x.type.ndim != 2 \
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101 or x.type.dtype not in ['float32', 'float64']:
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102 raise ValueError('x must be 2-d tensor of floats')
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103 if b.type.ndim != 1 \
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104 or x.type.dtype not in ['float32', 'float64']:
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105 raise ValueError('b must be 1-d tensor of floats')
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106 if y_idx.type.ndim != 1 \
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107 or y_idx.type.dtype not in ['int8', 'int16', 'int32', 'int64']:
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108 raise ValueError('y_idx must be 1-d tensor of ints')
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109
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110 # TODO: Is this correct? It used to be y, not y_idx
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111 nll = tensor.Tensor(x.type.dtype,
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112 y_idx.type.broadcastable).make_result()
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113 # nll = Tensor(x.dtype, y.broadcastable)
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114 sm = x.type.make_result()
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115 return theano.Apply(self, [x, b, y_idx], [nll, sm])
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116 def perform(self, node, input_storage, output_storage):
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117 x, b, y_idx = input_storage
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118 if b.shape[0] != x.shape[1]:
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119 raise ValueError('b must have same number of columns as x')
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120 if y_idx.shape[0] != x.shape[0]:
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121 raise ValueError('y_idx must have same number of rows as x')
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122
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123 sm = numpy.zeros_like(x) # softmax
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124 nll = numpy.zeros(x.shape[0]) #nll(y | softmax(x))
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125 for i in xrange(sm.shape[0]):
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126 row = x[i] + b
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127 sm[i] = numpy.exp(row - numpy.max(row)) #softmax
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128 sm[i] *= 1.0 / numpy.sum(sm[i]) #vector scale
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129 nll[i] = -numpy.log( sm[i, y_idx[i]]) #cross-entropy
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130 output_storage[0][0] = nll
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131 output_storage[1][0] = sm
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132 def grad(self, (x, b, y_idx), (g_nll, g_sm)):
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133 if g_sm is not None:
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134 raise NotImplementedError()
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135 nll, sm = crossentropy_softmax_1hot_with_bias(x, b, y_idx)
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136 dx = CrossentropySoftmax1HotWithBiasDx()(g_nll, sm, y_idx)
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137 db = tensor.sum(dx, axis = [0])
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138 return dx, db, None
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139
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140 def c_headers(self): return ['<iostream>']
181
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141 def c_code(self, node, name, (x, b, y_idx), (nll, sm), sub):
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142 # this implementation was lifted from
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143 # /u/bergstrj/cvs/bergstrj/src/feb07/nn.cxx
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144
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145 #TODO: put this into a templated function, in the support code
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146 #TODO: declare the max of each row as an Op output
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147
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148 #TODO: set error messages for failures in this code
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149
184
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150 #TODO: use this to accept float32 and int32: node.inputs[0].type.dtype_specs()[1]
185
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151 y_idx_type = node.inputs[2].type.dtype_specs()[1]
184
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152
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153 return """
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154 npy_intp* Nx = %(x)s->dimensions;
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155
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156 if (%(x)s->nd != 2)
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157 {
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158 PyErr_SetString(PyExc_ValueError, "a not 2d tensor");
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159 %(fail)s;
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160 }
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161 if (%(b)s->nd != 1)
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162 {
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163 PyErr_SetString(PyExc_ValueError, "b not 1d tensor");
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164 %(fail)s;
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165 }
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166 if (%(y_idx)s->nd != 1)
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167 {
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168 PyErr_SetString(PyExc_ValueError, "y_idx not 1d tensor");
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169 %(fail)s;
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170 }
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171 if (%(x)s->descr->type_num != PyArray_DOUBLE)
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172 {
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173 PyErr_SetString(PyExc_TypeError, "a not float64");
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174 %(fail)s;
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175 }
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176 if (%(b)s->descr->type_num != PyArray_DOUBLE)
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177 {
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178 PyErr_SetString(PyExc_TypeError, "b not float64");
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179 %(fail)s;
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180 }
185
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181 if ((%(y_idx)s->descr->type_num != PyArray_INT64)
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182 && (%(y_idx)s->descr->type_num != PyArray_INT32)
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183 && (%(y_idx)s->descr->type_num != PyArray_INT16)
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184 && (%(y_idx)s->descr->type_num != PyArray_INT8))
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185 {
185
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186 PyErr_SetString(PyExc_TypeError, "y_idx not int8, int16, int32, or int64");
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187 %(fail)s;
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188 }
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189 if ((%(x)s->dimensions[1] != %(b)s->dimensions[0])
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190 || (%(x)s->dimensions[0] != %(y_idx)s->dimensions[0]))
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191 {
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192 PyErr_SetString(PyExc_ValueError, "dimension mismatch in arguments");
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193 %(fail)s;
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194 }
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195
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196 if ((NULL == %(nll)s) //initial condition
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197 || (%(nll)s->dimensions[0] != %(y_idx)s->dimensions[0]))
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198 {
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199 if (NULL != %(nll)s) Py_XDECREF(%(nll)s);
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200 %(nll)s = (PyArrayObject*)PyArray_SimpleNew(1, PyArray_DIMS(%(y_idx)s), type_num_%(x)s);
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201 if(!%(nll)s)
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202 {
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203 PyErr_SetString(PyExc_MemoryError, "failed to alloc nll output");
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204 %(fail)s;
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205 }
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206 }
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207 if ((NULL == %(sm)s)
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208 || (%(sm)s->dimensions[0] != %(x)s->dimensions[0])
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209 || (%(sm)s->dimensions[1] != %(x)s->dimensions[1]))
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210 {
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211 if (NULL != %(sm)s) Py_XDECREF(%(sm)s);
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212 %(sm)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(x)s), type_num_%(x)s);
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213 if(!%(sm)s) {
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214 // The normal cleanup code will take care of %(nll)s
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215 // Py_XDECREF(%(nll)s); %(nll)s=NULL;
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216 PyErr_SetString(PyExc_MemoryError, "failed to alloc sm output");
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217 %(fail)s
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218 }
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219 }
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220
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221 for (size_t i = 0; i < Nx[0]; ++i)
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222 {
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223 size_t j;
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224 double sum = 0.0;
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225 bool discount_max = false;
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226
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227 const double* __restrict__ x_i = (double*)(%(x)s->data + %(x)s->strides[0] * i);
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228 const double* __restrict__ b_i = (double*)(%(b)s->data);
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229 const %(y_idx_type)s y_i = ((%(y_idx_type)s*)(%(y_idx)s->data + %(y_idx)s->strides[0] * i))[0];
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230 double* __restrict__ sm_i = (double*)(%(sm)s->data + %(sm)s->strides[0] * i);
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231 double* __restrict__ nll_i = (double*)(%(nll)s->data + %(nll)s->strides[0] * i);
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232
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233 npy_intp Sx = %(x)s->strides[1]/sizeof(double);
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234 npy_intp Sb = %(b)s->strides[0]/sizeof(double);
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235 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double);
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236
30
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237 size_t row_max_j=0;
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238 double row_max = x_i[0] + b_i[0];
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239 //try to compute sum and sm the easy way
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240 for (j = 0; j < Nx[1]; ++j)
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241 {
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242 double row_ij = x_i[j * Sx] + b_i[j * Sb];
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243 row_max_j = (row_ij > row_max) ? j : row_max_j;
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244 row_max = (row_ij > row_max) ? row_ij : row_max;
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245
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246 double sm_ij = exp(row_ij);
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247 sum += sm_ij;
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248 sm_i[j * Ssm] = sm_ij;
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249 }
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250 if ((0.0 == sum) || (isinf(sum)))
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251 {
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diff changeset
252 //our cheap trick didn't work... try again and do it better.
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253 discount_max = true;
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254 sum = 0.0; //reset sum and recompute....
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255 for (j = 0; j < Nx[1]; ++j)
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256 {
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diff changeset
257 double row_ij = x_i[j * Sx] + b_i[j * Sb];
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258
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259 double sm_ij = exp(row_ij - row_max);
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260 sum += sm_ij;
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261 sm_i[j * Ssm] = sm_ij;
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262 }
32
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263 if ( (0.0 == sum) || (isinf(sum)))
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264 {
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265 //that was our best...
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266 %(fail)s;
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267 }
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268 //if we still can't sum it up, we're screwed.
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269 //So far, this assertion has never failed...
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270 }
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271
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diff changeset
272 //cblas_dscal(x.N, 1.0 / sum, &mat_at(s,i,0), s.n);
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diff changeset
273 double sum_inv = 1.0 / sum;
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274 for (j = 0; j < Nx[1]; ++j)
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275 {
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276 sm_i[j * Ssm] *= sum_inv;
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277 }
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278
32
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diff changeset
279 if (y_i >= Nx[1])
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280 {
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diff changeset
281 %(fail)s;
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diff changeset
282 }
30
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283
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diff changeset
284 nll_i[0] = - x_i[y_i*Sx]
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285 - b_i[y_i*Sb]
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286 + (discount_max ? row_max : 0.0)
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287 + log(sum);
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288 //mat_at(y,i,0) = -log( mat_at(s,i,t[i])); //less accurate?
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289 //mat_at(y,i,0) = - mat_at(x,i,t[i]) - mat_at(b,0,t[i]) + (discount_max ? maxi : 0.0) + log(sum);
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290 }
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diff changeset
291 """ % dict(locals(), **sub)
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diff changeset
292 crossentropy_softmax_1hot_with_bias = CrossentropySoftmax1HotWithBias()
30
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293
117
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294 class CrossentropySoftmax1HotWithBiasDx (theano.Op):
30
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295 nin=3
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296 nout=1
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297 """Gradient wrt x of the CrossentropySoftmax1Hot Op"""
117
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298 def __init__(self, **kwargs):
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299 theano.Op.__init__(self,**kwargs)
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300 def make_node(self, dy, sm, y_idx,**kwargs):
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301 dy = tensor.as_tensor(dy)
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302 sm = tensor.as_tensor(sm)
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diff changeset
303 y_idx = tensor.as_tensor(y_idx)
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diff changeset
304 return theano.Apply(self, [dy, sm, y_idx],[sm.type.make_result()])
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diff changeset
305 def perform(self, node, input_storage, output_storage):
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diff changeset
306 dy,sm,y_idx = input_storage
30
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diff changeset
307 dx = numpy.zeros_like(sm)
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diff changeset
308 for i in xrange(sm.shape[0]):
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diff changeset
309 dx[i] = dy[i] * sm[i] #vector scale
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310 dx[i, y_idx[i]] -= dy[i] #scalar decrement
117
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diff changeset
311 output_storage[0][0] = dx
30
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diff changeset
312 def grad(self, *args):
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diff changeset
313 raise NotImplementedError()
181
1b06bc2c3ca9 fixed c_code for the ops in nnet_ops.py
Olivier Breuleux <breuleuo@iro.umontreal.ca>
parents: 121
diff changeset
314 def c_code(self, node, name, (dnll, sm, y_idx), (dx,), sub):
185
3d953844abd3 support for more int types in crossentropysoftmax1hot
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parents: 184
diff changeset
315 y_idx_type = node.inputs[2].type.dtype_specs()[1]
32
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diff changeset
316 return """
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diff changeset
317
67
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318 if ((%(dnll)s->descr->type_num != PyArray_DOUBLE)
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diff changeset
319 || (%(sm)s->descr->type_num != PyArray_DOUBLE)
185
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parents: 184
diff changeset
320 )
67
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diff changeset
321 {
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diff changeset
322 PyErr_SetString(PyExc_TypeError, "types should be float64, float64, int64");
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diff changeset
323 %(fail)s;
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diff changeset
324 }
185
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parents: 184
diff changeset
325 if ((%(y_idx)s->descr->type_num != PyArray_INT64)
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parents: 184
diff changeset
326 && (%(y_idx)s->descr->type_num != PyArray_INT32)
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parents: 184
diff changeset
327 && (%(y_idx)s->descr->type_num != PyArray_INT16)
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parents: 184
diff changeset
328 && (%(y_idx)s->descr->type_num != PyArray_INT8))
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diff changeset
329 {
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diff changeset
330 PyErr_SetString(PyExc_TypeError, "y_idx not int8, int16, int32, or int64");
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diff changeset
331 %(fail)s;
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diff changeset
332 }
67
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diff changeset
333 if ((%(dnll)s->nd != 1)
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334 || (%(sm)s->nd != 2)
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diff changeset
335 || (%(y_idx)s->nd != 1))
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diff changeset
336 {
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337 PyErr_SetString(PyExc_ValueError, "rank error");
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338 %(fail)s;
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339 }
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diff changeset
340 if ((%(dnll)s->dimensions[0] != %(sm)s->dimensions[0])
68
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341 || (%(dnll)s->dimensions[0] != %(y_idx)s->dimensions[0]))
67
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342 {
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343 PyErr_SetString(PyExc_ValueError, "dimension mismatch");
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344 %(fail)s;
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345 }
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346 if ((NULL == %(dx)s)
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diff changeset
347 || (%(dx)s->dimensions[0] != %(sm)s->dimensions[0])
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348 || (%(dx)s->dimensions[1] != %(sm)s->dimensions[1]))
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diff changeset
349 {
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diff changeset
350 if (NULL != %(dx)s) Py_XDECREF(%(dx)s);
68
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diff changeset
351 %(dx)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(sm)s), type_num_%(sm)s);
67
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diff changeset
352 if(!%(dx)s) {
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diff changeset
353 PyErr_SetString(PyExc_MemoryError, "failed to alloc dx output");
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354 %(fail)s
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diff changeset
355 }
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diff changeset
356 }
24
2e8be9f5412b added nnet_ops
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357
67
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diff changeset
358 for (size_t i = 0; i < %(dx)s->dimensions[0]; ++i)
32
039c0f249859 added C impl for softmax dx
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diff changeset
359 {
039c0f249859 added C impl for softmax dx
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diff changeset
360 const double dnll_i = ((double*)(%(dnll)s->data + %(dnll)s->strides[0] * i))[0];
039c0f249859 added C impl for softmax dx
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diff changeset
361
185
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diff changeset
362 const %(y_idx_type)s y_i = ((%(y_idx_type)s*)(%(y_idx)s->data + %(y_idx)s->strides[0] * i))[0];
32
039c0f249859 added C impl for softmax dx
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diff changeset
363
039c0f249859 added C impl for softmax dx
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diff changeset
364 const double* __restrict__ sm_i = (double*)(%(sm)s->data + %(sm)s->strides[0] * i);
039c0f249859 added C impl for softmax dx
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diff changeset
365 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double);
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diff changeset
366
039c0f249859 added C impl for softmax dx
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diff changeset
367 double* __restrict__ dx_i = (double*)(%(dx)s->data + %(dx)s->strides[0] * i);
039c0f249859 added C impl for softmax dx
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diff changeset
368 npy_intp Sdx = %(dx)s->strides[1]/sizeof(double);
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diff changeset
369
67
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diff changeset
370 for (size_t j = 0; j < %(dx)s->dimensions[1]; ++j)
32
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diff changeset
371 {
039c0f249859 added C impl for softmax dx
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diff changeset
372 dx_i[j * Sdx] = dnll_i * sm_i[j * Ssm];
039c0f249859 added C impl for softmax dx
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diff changeset
373 }
67
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diff changeset
374 if (y_i >= %(dx)s->dimensions[1])
32
039c0f249859 added C impl for softmax dx
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diff changeset
375 {
039c0f249859 added C impl for softmax dx
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diff changeset
376 %(fail)s;
039c0f249859 added C impl for softmax dx
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diff changeset
377 }
039c0f249859 added C impl for softmax dx
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diff changeset
378 dx_i[y_i * Sdx] -= dnll_i;
039c0f249859 added C impl for softmax dx
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diff changeset
379 }
039c0f249859 added C impl for softmax dx
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diff changeset
380 """ % dict(locals(), **sub)
69
8c2607f387e6 added softplus, elaborated sigmoid
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parents: 68
diff changeset
381
70
76e5c0f37165 better docs & precondition testing for cross_entropy_softmax_1hot & friends
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parents: 69
diff changeset
382 def crossentropy_softmax_1hot(x, y_idx, **kwargs):
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diff changeset
383 b = tensor.zeros_like(x[0,:])
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parents: 69
diff changeset
384 return crossentropy_softmax_1hot_with_bias(x, b, y_idx, **kwargs)
382
b4efd192d880 Moved xent loss to nnet_ups
Joseph Turian <turian@gmail.com>
parents: 381
diff changeset
385
b4efd192d880 Moved xent loss to nnet_ups
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parents: 381
diff changeset
386 def binary_crossentropy(output, target):
b4efd192d880 Moved xent loss to nnet_ups
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parents: 381
diff changeset
387 """
b4efd192d880 Moved xent loss to nnet_ups
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parents: 381
diff changeset
388 Compute the crossentropy of binary output wrt binary target.
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parents: 381
diff changeset
389 @note: We do not sum, crossentropy is computed by component.
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parents: 381
diff changeset
390 @todo: Rewrite as a scalar, and then broadcast to tensor.
b4efd192d880 Moved xent loss to nnet_ups
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parents: 381
diff changeset
391 """
383
344d1f874af7 Small fix
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parents: 382
diff changeset
392 return -(target * tensor.log(output) + (1 - target) * tensor.log(1 - output))
419
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
393
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
394
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
395
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
396 class Prepend_scalar_constant_to_each_row(theano.Op):
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diff changeset
397 def __init__(self, val = 0):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
398 if isinstance(val, float):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
399 val = scalar.constant(val)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
400 self.val = val
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
401
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
402 def make_node(self, mat):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
403 #check type of input
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
404 if not isinstance(mat,theano.Result) or not mat.type==tensor.matrix().type:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
405 raise TypeError("Expected a matrix as input")
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
406 x = tensor.as_tensor(mat)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
407 y = tensor.as_tensor(self.val)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
408 if x.type.dtype != y.type.dtype:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
409 TypeError("the value to prepend don't have the same type as the matrix")
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
410
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
411 node = theano.Apply(op=self, inputs=[mat], outputs=[tensor.matrix()])
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
412 return node
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
413
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
414 def perform(self, node, (mat, ), (output, )):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
415 new_shape=(mat.shape[0],mat.shape[1]+1)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
416 if output[0] == None:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
417 output[0]=numpy.empty(new_shape,dtype=mat.dtype)
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parents: 383
diff changeset
418 out=output[0]
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parents: 383
diff changeset
419 else:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
420 if output[0].shape!=new_shape:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
421 try:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
422 output[0].resize(new_shape)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
423 except:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
424 output[0]=numpy.empty(new_shape, dtype=mat.dtype)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
425 out=output[0]
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
426
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
427 out[:,0].fill(self.val.data)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
428 out[:,1:]=mat
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
429
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
430 def grad(self, (mat,), (goutput,)):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
431 return goutput[:,1:]
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parents: 383
diff changeset
432
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
433 class Prepend_scalar_to_each_row(theano.Op):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
434 def make_node(self, val, mat):
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parents: 383
diff changeset
435 #check type of input
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parents: 383
diff changeset
436 if isinstance(val, float):
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parents: 383
diff changeset
437 val = scalar.constant(val)
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parents: 383
diff changeset
438 if not isinstance(mat,theano.Result) or not mat.type==tensor.matrix().type:
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parents: 383
diff changeset
439 raise TypeError("Expected a matrix as input")
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
440 x = tensor.as_tensor(mat)
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parents: 383
diff changeset
441 y = tensor.as_tensor(val)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
442 if x.type.dtype != y.type.dtype:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
443 TypeError("the value to prepend don't have the same type as the matrix")
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
444
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
445 node = theano.Apply(op=self, inputs=[val,mat], outputs=[tensor.matrix()])
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
446 return node
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
447
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
448 def perform(self, node, (val,mat), (output, )):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
449 new_shape=(mat.shape[0],mat.shape[1]+1)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
450 if output[0] == None:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
451 output[0]=numpy.empty(new_shape,dtype=mat.dtype)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
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parents: 383
diff changeset
452 out=output[0]
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
453 else:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
454 if output[0].shape!=new_shape:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
455 try:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
456 output[0].resize(new_shape)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
457 except:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
458 output[0]=numpy.empty(new_shape, dtype=mat.dtype)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
459 out=output[0]
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
460 out[:,0].fill(val)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
461 out[:,1:]=mat
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
462
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
463 def grad(self, (val, mat), (goutput,)):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
464 return goutput[:,0], goutput[:,1:]
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
465
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
466 prepend_scalar_to_each_row = Prepend_scalar_to_each_row()
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
467 prepend_0_to_each_row = Prepend_scalar_constant_to_each_row(0.)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
468 prepend_1_to_each_row = Prepend_scalar_constant_to_each_row(1.)
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
469
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
470 class solve(theano.Op):
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
471 """
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
472 Find the solution to the linear equation Ax=b,
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
473 where A is a 2d matrix and b is a 1d or 2d matrix.
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James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
474 It use numpy.solve to find the solution.
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
475 """
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
476
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
477 def make_node(self, A, b):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
478 if not isinstance(A, theano.Result) or not A.type==tensor.matrix().type:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
479 raise TypeError("We expected that A had a matrix type")
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
480 if not isinstance(B, theano.Result) or not B.type==tensor.matrix().type:
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
481 raise TypeError("We expected that B had a matrix type")
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
482
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
483 node = theano.Apply(op=self, inputs=[A, B], outputs=[tensor.matrix()])
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
484 return node
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
485
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
486 def perform(self, node, (A, B), (output, )):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
487 ret=numpy.solve(A,B)
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
488 output[0]=ret
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
489
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
490 def grad(self, (theta, A, B), (gtheta,)):
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
491 raise NotImplementedError()
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
492
43d9aa93934e added other_ops.py to nnet_ops; added basic tests, no docs.
James Bergstra <bergstrj@iro.umontreal.ca>
parents: 383
diff changeset
493