| /external/tensorflow/tensorflow/python/keras/layers/preprocessing/benchmarks/ |
| D | image_preproc_benchmark.py | 47 inputs_shape = array_ops.shape(inputs)
48 batch_size = inputs_shape[0]
49 img_hd = math_ops.cast(inputs_shape[1], dtypes.float32)
50 img_wd = math_ops.cast(inputs_shape[2], dtypes.float32)
61 inputs_shape = array_ops.shape(inputs)
62 batch_size = inputs_shape[0]
63 img_hd = math_ops.cast(inputs_shape[1], dtypes.float32)
64 img_wd = math_ops.cast(inputs_shape[2], dtypes.float32)
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | ctc_decoder_ops.cc | 68 const TensorShape& inputs_shape = (*inputs)->shape(); in ValidateInputsGenerateOutputs() local
70 if (inputs_shape.dims() != 3) { in ValidateInputsGenerateOutputs()
74 const int64 max_time = inputs_shape.dim_size(0); in ValidateInputsGenerateOutputs()
75 const int64 batch_size = inputs_shape.dim_size(1); in ValidateInputsGenerateOutputs()
200 const TensorShape& inputs_shape = inputs->shape(); in Compute() local
203 const int64 max_time = inputs_shape.dim_size(0); in Compute()
204 const int64 batch_size = inputs_shape.dim_size(1); in Compute()
205 const int64 num_classes_raw = inputs_shape.dim_size(2); in Compute()
302 const TensorShape& inputs_shape = inputs->shape(); in Compute() local
304 const int64 max_time = inputs_shape.dim_size(0); in Compute()
[all …]
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| D | ctc_loss_op.cc | 106 const TensorShape& inputs_shape = inputs->shape(); in Compute() local
107 const int64 max_time = inputs_shape.dim_size(0); in Compute()
108 const int64 batch_size = inputs_shape.dim_size(1); in Compute()
109 const int64 num_classes_raw = inputs_shape.dim_size(2); in Compute()
182 ctx->allocate_output("gradient", inputs_shape, &gradient)); in Compute()
274 const TensorShape& inputs_shape = inputs->shape(); in Compute() local
275 const int64 max_time_raw = inputs_shape.dim_size(0); in Compute()
276 const int64 batch_size_raw = inputs_shape.dim_size(1); in Compute()
277 const int64 num_classes_raw = inputs_shape.dim_size(2); in Compute()
313 ctx->allocate_output("gradient", inputs_shape, &gradient)); in Compute()
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| /external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
| D | rnn_cell.py | 98 def build(self, inputs_shape): argument
107 if inputs_shape[-1] is None:
109 (inputs_shape,))
111 input_depth = inputs_shape[-1]
296 def build(self, inputs_shape): argument
306 if len(inputs_shape) != 2:
308 "inputs_shape must be 2-dimensional, saw shape: %s" % inputs_shape)
310 inputs_shape[1]
311 if isinstance(inputs_shape[1], int) else inputs_shape[1].value)
313 raise ValueError("Invalid inputs_shape, saw shape: %s" % inputs_shape)
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| /external/tensorflow/tensorflow/python/keras/layers/preprocessing/ |
| D | image_preprocessing.py | 152 inputs_shape = array_ops.shape(inputs)
153 img_hd = inputs_shape[H_AXIS]
154 img_wd = inputs_shape[W_AXIS]
537 inputs_shape = array_ops.shape(inputs)
538 batch_size = inputs_shape[0]
540 img_hd = math_ops.cast(inputs_shape[h_axis], dtypes.float32)
541 img_wd = math_ops.cast(inputs_shape[w_axis], dtypes.float32)
826 inputs_shape = array_ops.shape(inputs)
827 batch_size = inputs_shape[0]
828 img_hd = math_ops.cast(inputs_shape[H_AXIS], dtypes.float32)
[all …]
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| /external/tensorflow/tensorflow/lite/micro/kernels/ |
| D | concatenation.cc | 89 RuntimeShape inputs_shape[kMaxInputNum]; in EvalUnquantized() local
92 GetAllInputTensorShapes(context, node, inputs_shape); in EvalUnquantized()
93 GetShapesPointers(inputs_shape, node->inputs->size, inputs_shape_ptr); in EvalUnquantized()
109 RuntimeShape inputs_shape[kMaxInputNum]; in EvalQuantizedUInt8() local
112 GetAllInputTensorShapes(context, node, inputs_shape); in EvalQuantizedUInt8()
113 GetShapesPointers(inputs_shape, node->inputs->size, inputs_shape_ptr); in EvalQuantizedUInt8()
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| /external/tensorflow/tensorflow/python/keras/layers/legacy_rnn/ |
| D | rnn_cell_impl.py | 458 def build(self, inputs_shape): argument
459 if inputs_shape[-1] is None:
461 str(inputs_shape))
464 input_depth = inputs_shape[-1]
568 def build(self, inputs_shape): argument
569 if inputs_shape[-1] is None:
571 str(inputs_shape))
573 input_depth = inputs_shape[-1]
746 def build(self, inputs_shape): argument
747 if inputs_shape[-1] is None:
[all …]
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| D | rnn_cell_wrapper_impl.py | 197 def build(self, inputs_shape): argument
198 self.cell.build(inputs_shape)
|
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | rnn_cell_wrapper_v2.py | 74 def build(self, inputs_shape): argument
76 self.cell.build(inputs_shape)
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| D | convolutional.py | 999 inputs_shape = array_ops.shape(inputs)
1000 batch_size = inputs_shape[0]
1006 length = inputs_shape[t_axis]
1270 inputs_shape = array_ops.shape(inputs)
1271 batch_size = inputs_shape[0]
1286 height = height if height is not None else inputs_shape[h_axis]
1287 width = width if width is not None else inputs_shape[w_axis]
1580 inputs_shape = array_ops.shape(inputs)
1581 batch_size = inputs_shape[0]
1587 depth = inputs_shape[d_axis]
[all …]
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| D | recurrent_test.py | 1859 def build(self, inputs_shape): argument
1862 input_1 = inputs_shape.t1[1]
1863 input_2, input_3 = inputs_shape.t2[1:]
1865 input_1 = inputs_shape[0][1]
1866 input_2, input_3 = inputs_shape[1][1:]
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.nn.-r-n-n-cell-device-wrapper.pbtxt | 171 argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
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| D | tensorflow.nn.-r-n-n-cell-residual-wrapper.pbtxt | 171 argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
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| D | tensorflow.nn.-r-n-n-cell-dropout-wrapper.pbtxt | 175 argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
|
| /external/tensorflow/tensorflow/core/grappler/optimizers/ |
| D | arithmetic_optimizer_test.cc | 837 Output inputs_shape = ops::Shape(s, inputs); in TEST_F() local
840 Output batch_size = ops::Slice(s, inputs_shape, ops::Const(s, {0}, {1}), in TEST_F()
879 Output inputs_shape = ops::Shape(s, inputs); in TEST_F() local
882 Output batch_size = ops::Slice(s, inputs_shape, ops::Const(s, {0}, {1}), in TEST_F()
884 Output height = ops::Slice(s, inputs_shape, ops::Const(s, {2}, {1}), in TEST_F()
886 Output width = ops::Slice(s, inputs_shape, ops::Const(s, {3}, {1}), in TEST_F()
1342 Output inputs_shape = in TEST_F() local
1345 ops::RandomUniform(s.WithOpName("inputs"), inputs_shape, DT_FLOAT); in TEST_F()
1406 Output inputs_shape = in TEST_F() local
1484 Output inputs_shape = in TEST_F() local
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.nn.rnn_cell.-dropout-wrapper.pbtxt | 184 argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
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| D | tensorflow.lite.experimental.nn.-tf-lite-r-n-n-cell.pbtxt | 179 argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
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| D | tensorflow.lite.experimental.nn.-t-f-lite-l-s-t-m-cell.pbtxt | 179 argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
|