| /external/tensorflow/tensorflow/contrib/kfac/python/ops/ |
| D | fisher_blocks.py | 347 self._inputs = []
354 inputs = _concat_along_batch_dim(self._inputs)
409 self._inputs.append(inputs)
414 result = len(self._inputs)
457 self._inputs = []
470 inputs = _concat_along_batch_dim(self._inputs)
511 self._inputs.append(inputs)
516 return len(self._inputs)
611 self._inputs = []
631 inputs = _concat_along_batch_dim(self._inputs)
[all …]
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| D | fisher_factors.py | 859 self._inputs = inputs
870 (self._inputs,) + tuple(self._outputs_grads))
874 input_size = self._inputs.shape[1] + self._has_bias
894 inputs = self._inputs
896 inputs = append_homog(self._inputs)
932 self._inputs = inputs
945 (self._inputs,) + tuple(self._outputs_grads))
964 with maybe_colocate_with(self._inputs):
970 self._inputs,
1084 self._inputs = inputs
[all …]
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | lstm_test.py | 61 self._inputs = np.array([[-1.], [-.5], [0.], [.5], [1.]], np.float32)
62 self._batch_size = len(self._inputs)
83 x = constant_op.constant(self._inputs)
115 self.assertAllClose(m, self._NextM(self._inputs, 1., m_prev, c_prev))
116 self.assertAllClose(c, self._NextC(self._inputs, 1., m_prev, c_prev))
128 self._NextM(self._inputs, weight, m_prev, c_prev))
130 self._NextC(self._inputs, weight, m_prev, c_prev))
147 x_seq = [constant_op.constant(self._inputs)] * seq_length
167 x_seq = [constant_op.constant(self._inputs)] * seq_length
200 m0 = self._NextM(self._inputs, weight1, m_init, c_init)
[all …]
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| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| D | training_test.py | 89 self._inputs = np.random.rand(16, 4).astype(np.float32)
94 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
108 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
111 expected_mean = np.mean(self._inputs, axis=(0))
112 expected_var = np.var(self._inputs, axis=(0))
145 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
178 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
201 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
228 self._inputs = np.zeros((16, 4))
233 self._inputs[i, j] = 1
[all …]
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| D | evaluation_test.py | 150 self._inputs = np.zeros((16, 4))
155 self._inputs[i, j] = 1
169 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
194 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
220 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
247 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
268 self._inputs = np.zeros((16, 4))
273 self._inputs[i, j] = 1
287 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
309 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
[all …]
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| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| D | learning_test.py | 232 self._inputs = np.zeros((16, 4))
237 self._inputs[i, j] = 1
245 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
266 self._inputs = np.random.rand(16, 4).astype(np.float32)
277 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
280 expected_mean = np.mean(self._inputs, axis=(0))
281 expected_var = np.var(self._inputs, axis=(0))
315 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
348 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
373 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
[all …]
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| D | evaluation_test.py | 87 self._inputs = constant_op.constant(inputs, dtype=dtypes.float32)
89 self._predictions, self._scale = TestModel(self._inputs)
225 self._inputs = constant_op.constant(inputs, dtype=dtypes.float32)
227 self._predictions, self._scale = TestModel(self._inputs)
|
| /external/tensorflow/tensorflow/python/training/ |
| D | evaluation_test.py | 68 self._inputs = np.zeros((16, 4))
73 self._inputs[i, j] = 1
87 tf_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
115 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
140 all_inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
176 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
204 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
233 inputs = constant_op.constant(self._inputs, dtype=dtypes.float32)
|
| /external/tensorflow/tensorflow/contrib/nn/python/ops/ |
| D | sampling_ops_test.py | 139 def _inputs(self): member in RankSampledSoftmaxLossTest
157 inputs=self._inputs(),
176 inputs=self._inputs(),
194 inputs=self._inputs(),
210 inputs=self._inputs(),
223 inputs=self._inputs(),
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | clustering_ops.py | 144 self._inputs = inputs if isinstance(inputs, list) else [inputs]
365 inputs = self._inputs
370 self._inputs, num_clusters, initial_clusters, self._distance_metric,
587 self._inputs = inputs
601 [array_ops.shape(i)[0] for i in self._inputs])
610 return embedding_lookup(self._inputs, indices, partition_strategy='div')
615 inp = self._inputs[0]
638 first_shard = self._inputs[0]
713 lambda: array_ops.concat(self._inputs, 0),
731 return self._initial_clusters(self._inputs, self._num_remaining)
|
| /external/tensorflow/tensorflow/contrib/quantize/python/ |
| D | graph_matcher.py | 56 self._inputs = [
74 if not self._inputs:
78 if len(op.inputs) != len(self._inputs):
81 for input_tensor, input_pattern in zip(op.inputs, self._inputs):
|
| /external/opencv/ml/src/ |
| D | mlann_mlp.cpp | 266 float CvANN_MLP::predict( const CvMat* _inputs, CvMat* _outputs ) const in predict() argument
278 if( !CV_IS_MAT(_inputs) || !CV_IS_MAT(_outputs) || in predict()
279 !CV_ARE_TYPES_EQ(_inputs,_outputs) || in predict()
280 CV_MAT_TYPE(_inputs->type) != CV_32FC1 && in predict()
281 CV_MAT_TYPE(_inputs->type) != CV_64FC1 || in predict()
282 _inputs->rows != _outputs->rows ) in predict()
286 if( _inputs->cols != layer_sizes->data.i[0] ) in predict()
293 n = dn0 = _inputs->rows; in predict()
312 cvGetRows( _inputs, layer_in, i, i + dn ); in predict()
686 bool CvANN_MLP::prepare_to_train( const CvMat* _inputs, const CvMat* _outputs, in prepare_to_train() argument
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| /external/toolchain-utils/fdo_scripts/ |
| D | divide_and_merge_profiles.py | 24 self._inputs = inputs
47 for i in self._inputs:
71 for i in self._inputs:
|
| /external/tensorflow/tensorflow/python/debug/lib/ |
| D | debug_graphs.py | 175 self._inputs = []
212 self._inputs.append(inp)
219 return self._inputs
|
| /external/tensorflow/tensorflow/python/framework/ |
| D | ops.py | 2010 self._inputs = inputs
2013 return iter(self._inputs)
2016 return len(self._inputs)
2019 return bool(self._inputs)
2025 return self._inputs[i]
2044 def _inputs(self): member in Operation
2049 @_inputs.setter
2050 def _inputs(self, value): member in Operation
|
| /external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
| D | helper.py | 187 self._inputs = inputs
206 return self._inputs
|
| /external/opencv/ml/include/ |
| D | ml.h | 1181 virtual int train( const CvMat* _inputs, const CvMat* _outputs,
1185 virtual float predict( const CvMat* _inputs,
1209 virtual bool prepare_to_train( const CvMat* _inputs, const CvMat* _outputs,
|
| /external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/ |
| D | cudnn_rnn_test.py | 98 self._inputs = array_ops.placeholder(
130 self._inputs, initial_state=self._initial_state, training=training)
140 return self._inputs
|
| /external/v8/src/ |
| D | v8.gyp | 2221 'python', '<@(_inputs)', '<(PRODUCT_DIR)/natives_blob_host.bin'
2228 'python', '<@(_inputs)', '<(PRODUCT_DIR)/natives_blob.bin'
2237 'python', '<@(_inputs)', '<(PRODUCT_DIR)/natives_blob.bin'
|
| /external/tensorflow/tensorflow/contrib/lite/schema/ |
| D | schema_generated.h | 5474 auto _inputs = _o->inputs.size() ? _fbb.CreateVector(_o->inputs) : 0;
5483 _inputs,
5516 auto _inputs = _o->inputs.size() ? _fbb.CreateVector(_o->inputs) : 0;
5523 _inputs,
|