Searched refs:inp_shape (Results 1 – 5 of 5) sorted by relevance
| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | gradients.py | 123 inp_shape = array_ops.shape(inp)
126 [check_ops.assert_equal(batch_size, inp_shape[0])]):
146 new_shape = array_ops.concat([output_shape, inp_shape[1:]], axis=0)
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| D | pfor.py | 1794 inp_shape = array_ops.shape(inp)
1801 new_shape = [n[0], block_size, inp_shape[1] // block_size, -1]
1806 new_shape = array_ops.concat([n * inp_shape[1], inp_shape[2:]], axis=0)
1821 inp_shape = array_ops.shape(inp)
1830 [n, block_size * inp_shape[1:2], output_shape[1:]], axis=0)
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | concat_op.cc | 171 const TensorShape inp_shape = ctx->InputShape(1 + i); in Compile() local
172 OP_REQUIRES(ctx, inp0_rank == inp_shape.num_elements(), in Compile()
175 inp_shape.num_elements())); in Compile()
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| /external/tensorflow/tensorflow/python/keras/layers/preprocessing/ |
| D | category_crossing.py | 179 for inp_shape in input_shapes:
180 inp_tensor_shape = tensor_shape.TensorShape(inp_shape).as_list()
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_integration_test.py | 106 for layer_type, inp_shape, fuzz_dims, arg_dict, filter_fn in _LAYERS_TO_TEST:
115 cases.append((name, layer_type, inp_shape, fuzz_dims, layer_kwargs))
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