| /external/tensorflow/tensorflow/c/eager/ |
| D | c_api_debug.cc | 69 xla::Shape padded_shape; in TFE_TensorHandleTensorDebugInfo() local
70 status->status = shape_fn(*tensor, &padded_shape); in TFE_TensorHandleTensorDebugInfo()
82 << padded_shape.DebugString(); in TFE_TensorHandleTensorDebugInfo()
86 if (padded_shape.IsTuple()) { in TFE_TensorHandleTensorDebugInfo()
87 if (xla::ShapeUtil::TupleElementCount(padded_shape) != 2) { in TFE_TensorHandleTensorDebugInfo()
93 padded_shape.DebugString()); in TFE_TensorHandleTensorDebugInfo()
99 xla::Shape shape0 = xla::ShapeUtil::GetTupleElementShape(padded_shape, 0); in TFE_TensorHandleTensorDebugInfo()
101 xla::ShapeUtil::GetTupleElementShape(padded_shape, 1); in TFE_TensorHandleTensorDebugInfo()
105 padded_shape.DebugString()); in TFE_TensorHandleTensorDebugInfo()
111 padded_shape.DebugString()); in TFE_TensorHandleTensorDebugInfo()
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| /external/tensorflow/tensorflow/python/data/experimental/ops/ |
| D | batching.py | 206 def padded_batch_window(dataset, padded_shape, padding_value=None): argument
232 return _padded_batch_dense_window(dataset, padded_shape, padding_value)
236 return _padded_batch_sparse_window(dataset, padded_shape)
241 def _padded_batch_dense_window(dataset, padded_shape, padding_value=None): argument
244 padded_shape = math_ops.cast(
245 convert.partial_shape_to_tensor(padded_shape), dtypes.int32)
251 return padded_shape
257 math_ops.less_equal(array_ops.shape(value), padded_shape),
258 math_ops.equal(padded_shape, -1)))
261 array_ops.shape(value), padded_shape
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SpaceToBatchND.pbtxt | 27 input according to `paddings` to produce `padded` of shape `padded_shape`.
32 [padded_shape[1] / block_shape[0],
35 padded_shape[M] / block_shape[M-1],
44 [padded_shape[1] / block_shape[0],
46 padded_shape[M] / block_shape[M-1]] +
53 [padded_shape[1] / block_shape[0],
55 padded_shape[M] / block_shape[M-1]] +
|
| /external/tensorflow/tensorflow/core/kernels/data/ |
| D | padded_batch_dataset_op.cc | 64 PartialTensorShape padded_shape; in MakeDataset() local
67 padded_shape_t.NumElements(), &padded_shape)); in MakeDataset()
68 padded_shapes.push_back(std::move(padded_shape)); in MakeDataset()
275 const PartialTensorShape& padded_shape = in GetNextInternal() local
278 for (int dim = 0; dim < padded_shape.dims(); ++dim) { in GetNextInternal()
279 if (padded_shape.dim_size(dim) == -1) { in GetNextInternal()
282 batch_component_shape.AddDim(padded_shape.dim_size(dim)); in GetNextInternal()
291 if (element_shape.dims() != padded_shape.dims()) { in GetNextInternal()
295 component_index, ": expected rank ", padded_shape.dims(), in GetNextInternal()
298 for (int dim = 0; dim < padded_shape.dims(); ++dim) { in GetNextInternal()
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | spacetobatch_op.cc | 54 std::vector<int64> padded_shape(input_shape.begin(), input_shape.end()); in SpaceToBatch() local
65 padded_shape[1 + i] += pad_start + pad_end; in SpaceToBatch()
92 OP_REQUIRES(ctx, padded_shape[1 + i] % block_shape[i] == 0, in SpaceToBatch()
94 "]=", padded_shape[1 + i], in SpaceToBatch()
98 reshaped_padded_shape[1 + i * 2] = padded_shape[1 + i] / block_shape[i]; in SpaceToBatch()
139 output_shape[1 + i] = padded_shape[1 + i] / block_shape[i]; in SpaceToBatch()
|
| /external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
| D | resolve_constant_slice.cc | 66 Shape padded_shape = input_array.shape(); in Slice() local
67 while (padded_shape.dimensions_count() < 4) { in Slice()
68 padded_shape.mutable_dims()->insert(padded_shape.mutable_dims()->begin(), in Slice()
78 input_data[Offset(padded_shape, {in_b, in_h, in_w, in_d})]; in Slice()
|
| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
| D | padded_batch_dataset_serialization_test.py | 52 padded_shape = [-1]
56 padded_shapes=(padded_shape, padded_shape),
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | conv_ops_fused_image_transform.cc | 712 TensorShape padded_shape; in Compute() local
741 padded_shape.AddDim(before + resized_shape.dim_size(d) + after); in Compute()
764 OP_REQUIRES(context, padded_shape.dims() == 4, in Compute()
766 padded_shape.DebugString())); in Compute()
782 const int64 in_depth = padded_shape.dim_size(3); in Compute()
793 const int64 padded_rows_raw = padded_shape.dim_size(1); in Compute()
804 const int64 padded_cols_raw = padded_shape.dim_size(2); in Compute()
814 const int64 batch_raw = padded_shape.dim_size(0); in Compute()
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| /external/tensorflow/tensorflow/python/data/ops/ |
| D | dataset_ops.py | 2790 def _is_padded_shape_compatible_with(padded_shape, input_component_shape): argument
2802 if padded_shape.dims is None or input_component_shape.dims is None:
2804 if len(padded_shape.dims) != len(input_component_shape.dims):
2807 padded_shape.dims, input_component_shape.dims):
2814 def _padded_shape_to_tensor(padded_shape, input_component_shape): argument
2833 padded_shape_as_shape = tensor_shape.as_shape(padded_shape)
2843 ret = ops.convert_to_tensor(padded_shape, preferred_dtype=dtypes.int64)
2847 "shape was %s." % (padded_shape, ret.shape))
2851 "element type was %s." % (padded_shape, ret.dtype.name))
2927 for input_component_shape, padded_shape in zip(
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| /external/tensorflow/tensorflow/python/tpu/ |
| D | tpu.py | 613 padded_shape = padded_shapes[idx]
617 input_shape.assert_is_compatible_with(padded_shape)
637 for i, s in enumerate(padded_shape):
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| D | tpu_estimator.py | 3650 padded_shape = (batch_size,) + tuple(tensor.shape[1:])
3652 padded_tensor.set_shape(padded_shape)
|
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| D | sequence_queueing_state_saver.py | 1623 padded_shape = array_ops.concat(
1629 dense_shape=padded_shape)
|
| /external/tensorflow/tensorflow/python/ops/ |
| D | image_ops_impl.py | 733 padded_shape = [
737 padded.set_shape(padded_shape)
|