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comparison nnet_ops.py @ 67:810a8e3c85e1

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fixed horrible memory leak from crossentropy...
author bergstra@is23.m
date Fri, 18 Apr 2008 03:35:58 -0400
parents 1b152f46ad0c
children 315eb36ff954
comparison
equal deleted inserted replaced
35:2508c373cf29 67:810a8e3c85e1
69 nll, sm = crossentropy_softmax_1hot(x, b, y_idx) 69 nll, sm = crossentropy_softmax_1hot(x, b, y_idx)
70 dx = CrossentropySoftmax1HotDx(g_nll, sm, y_idx).outputs[0] 70 dx = CrossentropySoftmax1HotDx(g_nll, sm, y_idx).outputs[0]
71 db = tensor.Sum(dx, axis = [0]).outputs[0] 71 db = tensor.Sum(dx, axis = [0]).outputs[0]
72 return dx, db, None 72 return dx, db, None
73 73
74 def c_validate_cleanup(self, (x, b, y_idx), (nll, sm), sub): 74 def c_headers(self): return ['<iostream>']
75 """Not sure..."""
76 return ""
77 def c_support_code(self):
78 return """
79 """
80 def c_code(self, (x, b, y_idx), (nll, sm), sub): 75 def c_code(self, (x, b, y_idx), (nll, sm), sub):
81 # this implementation was lifted from 76 # this implementation was lifted from
82 # /u/bergstrj/cvs/bergstrj/src/feb07/nn.cxx 77 # /u/bergstrj/cvs/bergstrj/src/feb07/nn.cxx
83 78
84 #TODO: put this into a templated function, in the support code 79 #TODO: put this into a templated function, in the support code
87 #TODO: set error messages for failures in this code 82 #TODO: set error messages for failures in this code
88 83
89 return """ 84 return """
90 npy_intp* Nx = %(x)s->dimensions; 85 npy_intp* Nx = %(x)s->dimensions;
91 86
92 if (%(x)s->nd != 2) { %(fail)s } 87 if (%(x)s->nd != 2)
93 if (%(b)s->nd != 1) { %(fail)s } 88 {
94 if (%(y_idx)s->nd != 1) { %(fail)s } 89 PyErr_SetString(PyExc_ValueError, "a not 2d tensor");
95 if (%(x)s->descr->type_num != PyArray_DOUBLE) { %(fail)s} 90 %(fail)s;
96 if (%(b)s->descr->type_num != PyArray_DOUBLE) { %(fail)s} 91 }
97 if (%(y_idx)s->descr->type_num != PyArray_INT64) { %(fail)s} 92 if (%(b)s->nd != 1)
98 93 {
99 %(nll)s = (PyArrayObject*)PyArray_SimpleNew(1, PyArray_DIMS(%(y_idx)s), type_num_%(x)s); 94 PyErr_SetString(PyExc_ValueError, "b not 1d tensor");
100 if(!%(nll)s){%(fail)s} 95 %(fail)s;
101 96 }
102 %(sm)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(x)s), type_num_%(x)s); 97 if (%(y_idx)s->nd != 1)
103 if(!%(sm)s) { 98 {
104 // The normal cleanup code will take care of %(nll)s 99 PyErr_SetString(PyExc_ValueError, "y_idx not 1d tensor");
105 // Py_XDECREF(%(nll)s); %(nll)s=NULL; 100 %(fail)s;
106 %(fail)s 101 }
107 } 102 if (%(x)s->descr->type_num != PyArray_DOUBLE)
108 if (%(x)s->dimensions[1] != %(b)s->dimensions[0]) {%(fail)s} 103 {
109 if (%(sm)s->dimensions[0] != %(x)s->dimensions[0]) {%(fail)s} 104 PyErr_SetString(PyExc_TypeError, "a not float64");
110 if (%(sm)s->dimensions[1] != %(x)s->dimensions[1]) {%(fail)s} 105 %(fail)s;
106 }
107 if (%(b)s->descr->type_num != PyArray_DOUBLE)
108 {
109 PyErr_SetString(PyExc_TypeError, "b not float64");
110 %(fail)s;
111 }
112 if (%(y_idx)s->descr->type_num != PyArray_INT64)
113 {
114 PyErr_SetString(PyExc_TypeError, "y_idx not int64");
115 %(fail)s;
116 }
117 if ((%(x)s->dimensions[1] != %(b)s->dimensions[0])
118 || (%(x)s->dimensions[0] != %(y_idx)s->dimensions[0]))
119 {
120 PyErr_SetString(PyExc_ValueError, "dimension mismatch in arguments");
121 %(fail)s;
122 }
123
124 if ((NULL == %(nll)s) //initial condition
125 || (%(nll)s->dimensions[0] != %(y_idx)s->dimensions[0]))
126 {
127 if (NULL != %(nll)s) Py_XDECREF(%(nll)s);
128 %(nll)s = (PyArrayObject*)PyArray_SimpleNew(1, PyArray_DIMS(%(y_idx)s), type_num_%(x)s);
129 if(!%(nll)s)
130 {
131 PyErr_SetString(PyExc_MemoryError, "failed to alloc nll output");
132 %(fail)s;
133 }
134 }
135 if ((NULL == %(sm)s)
136 || (%(sm)s->dimensions[0] != %(x)s->dimensions[0])
137 || (%(sm)s->dimensions[1] != %(x)s->dimensions[1]))
138 {
139 if (NULL != %(sm)s) Py_XDECREF(%(sm)s);
140 %(sm)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(x)s), type_num_%(x)s);
141 if(!%(sm)s) {
142 // The normal cleanup code will take care of %(nll)s
143 // Py_XDECREF(%(nll)s); %(nll)s=NULL;
144 PyErr_SetString(PyExc_MemoryError, "failed to alloc sm output");
145 %(fail)s
146 }
147 }
111 148
112 for (size_t i = 0; i < Nx[0]; ++i) 149 for (size_t i = 0; i < Nx[0]; ++i)
113 { 150 {
114 size_t j; 151 size_t j;
115 double sum = 0.0; 152 double sum = 0.0;
202 dx[i] = dy[i] * sm[i] #vector scale 239 dx[i] = dy[i] * sm[i] #vector scale
203 dx[i, y_idx[i]] -= dy[i] #scalar decrement 240 dx[i, y_idx[i]] -= dy[i] #scalar decrement
204 self.outputs[0].data = dx 241 self.outputs[0].data = dx
205 def grad(self, *args): 242 def grad(self, *args):
206 raise NotImplementedError() 243 raise NotImplementedError()
207 def c_validate_update(self, (dnll, sm, y_idx), (dx,), sub):
208 """Allocate output storage"""
209 return """
210 if (%(dnll)s->nd != 1) { %(fail)s }
211 if (%(sm)s->nd != 2) { %(fail)s }
212 if (%(y_idx)s->nd != 1) { %(fail)s }
213 if (%(dnll)s->descr->type_num != PyArray_DOUBLE) { %(fail)s}
214 if (%(sm)s->descr->type_num != PyArray_DOUBLE) { %(fail)s}
215 if (%(y_idx)s->descr->type_num != PyArray_INT64) { %(fail)s}
216
217 %(dx)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(sm)s), type_num_%(sm)s);
218 if(!%(dx)s){%(fail)s}
219
220 """ % dict(locals(), **sub)
221 def c_validate_cleanup(self, inputs, outputs, sub):
222 """Not sure..."""
223 return ""
224 def c_support_code(self):
225 return """
226 """
227 def c_code(self, (dnll, sm, y_idx), (dx,), sub): 244 def c_code(self, (dnll, sm, y_idx), (dx,), sub):
228 return """ 245 return """
229 npy_intp* shape = %(dx)s->dimensions; 246
230 if (%(dnll)s->dimensions[0] != %(sm)s->dimensions[0]) {%(fail)s} 247 if ((%(dnll)s->descr->type_num != PyArray_DOUBLE)
231 if (%(dnll)s->dimensions[0] != %(y_idx)s->dimensions[0]) {%(fail)s} 248 || (%(sm)s->descr->type_num != PyArray_DOUBLE)
232 if (%(dnll)s->dimensions[0] != %(dx)s->dimensions[0]) {%(fail)s} 249 || (%(y_idx)s->descr->type_num != PyArray_INT64))
233 250 {
234 if (%(sm)s->dimensions[1] != %(dx)s->dimensions[1]) {%(fail)s} 251 PyErr_SetString(PyExc_TypeError, "types should be float64, float64, int64");
235 252 %(fail)s;
236 for (size_t i = 0; i < shape[0]; ++i) 253 }
254 if ((%(dnll)s->nd != 1)
255 || (%(sm)s->nd != 2)
256 || (%(y_idx)s->nd != 1))
257 {
258 PyErr_SetString(PyExc_ValueError, "rank error");
259 %(fail)s;
260 }
261 if ((%(dnll)s->dimensions[0] != %(sm)s->dimensions[0])
262 || (%(dnll)s->dimensions[0] != %(y_idx)s->dimensions[0])
263 || (%(dnll)s->dimensions[0] != %(dx)s->dimensions[0]))
264 {
265 PyErr_SetString(PyExc_ValueError, "dimension mismatch");
266 %(fail)s;
267 }
268 if ((NULL == %(dx)s)
269 || (%(dx)s->dimensions[0] != %(sm)s->dimensions[0])
270 || (%(dx)s->dimensions[1] != %(sm)s->dimensions[1]))
271 {
272 if (NULL != %(dx)s) Py_XDECREF(%(dx)s);
273 %(dx)s = (PyArrayObject*)PyArray_SimpleNew(2, PyArray_DIMS(%(x)s), type_num_%(x)s);
274 if(!%(dx)s) {
275 // The normal cleanup code will take care of %(nll)s
276 // Py_XDECREF(%(nll)s); %(nll)s=NULL;
277 PyErr_SetString(PyExc_MemoryError, "failed to alloc dx output");
278 %(fail)s
279 }
280 }
281
282 for (size_t i = 0; i < %(dx)s->dimensions[0]; ++i)
237 { 283 {
238 const double dnll_i = ((double*)(%(dnll)s->data + %(dnll)s->strides[0] * i))[0]; 284 const double dnll_i = ((double*)(%(dnll)s->data + %(dnll)s->strides[0] * i))[0];
239 285
240 const long int y_i = ((long int*)(%(y_idx)s->data + %(y_idx)s->strides[0] * i))[0]; 286 const long int y_i = ((long int*)(%(y_idx)s->data + %(y_idx)s->strides[0] * i))[0];
241 287
243 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double); 289 npy_intp Ssm = %(sm)s->strides[1]/sizeof(double);
244 290
245 double* __restrict__ dx_i = (double*)(%(dx)s->data + %(dx)s->strides[0] * i); 291 double* __restrict__ dx_i = (double*)(%(dx)s->data + %(dx)s->strides[0] * i);
246 npy_intp Sdx = %(dx)s->strides[1]/sizeof(double); 292 npy_intp Sdx = %(dx)s->strides[1]/sizeof(double);
247 293
248 for (size_t j = 0; j < shape[1]; ++j) 294 for (size_t j = 0; j < %(dx)s->dimensions[1]; ++j)
249 { 295 {
250 dx_i[j * Sdx] = dnll_i * sm_i[j * Ssm]; 296 dx_i[j * Sdx] = dnll_i * sm_i[j * Ssm];
251 } 297 }
252 if (y_i >= shape[1]) 298 if (y_i >= %(dx)s->dimensions[1])
253 { 299 {
254 %(fail)s; 300 %(fail)s;
255 } 301 }
256 dx_i[y_i * Sdx] -= dnll_i; 302 dx_i[y_i * Sdx] -= dnll_i;
257 } 303 }