| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | gradients.py | 48 flat_inputs = nest.flatten(inputs)
55 return gradient_ops.gradients(y, flat_inputs)
68 [output.dtype] * len(flat_inputs),
77 out.set_shape(output_tensor_shape.concatenate(flat_inputs[i].shape))
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| /external/tensorflow/tensorflow/python/compiler/xla/ |
| D | xla.py | 341 flat_inputs = nest.flatten(inputs)
343 flat_inputs = [ops.convert_to_tensor(x) for x in flat_inputs]
353 flat_inputs = [
355 for i, x in enumerate(flat_inputs)
360 structure=inputs, flat_sequence=flat_inputs)
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | data_adapter.py | 238 flat_inputs = nest.flatten(x)
240 flat_inputs += nest.flatten(y)
251 return all(_is_tensor(v) for v in flat_inputs)
442 flat_inputs = nest.flatten(x)
444 flat_inputs += nest.flatten(y)
457 return all(_is_array_like(v) for v in flat_inputs)
485 flat_inputs = nest.flatten(inputs)
491 flat_dtypes = [inp.dtype for inp in flat_inputs]
505 return [slice_array(inp) for inp in flat_inputs]
508 for v, original_inp in zip(flat_out, flat_inputs):
[all …]
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| D | training_generator_v1.py | 538 flat_inputs = nest.flatten(data)
539 if hasattr(flat_inputs[0], 'shape'):
540 return int(flat_inputs[0].shape[0]), False
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| D | training_v1.py | 2382 flat_inputs = nest.flatten(x, expand_composites=False)
2385 for (a, b) in zip(flat_inputs, flat_expected_inputs):
2402 flat_inputs = nest.flatten(x_shapes, expand_composites=False)
2404 for (a, b) in zip(flat_inputs, flat_expected_inputs):
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| D | training.py | 2492 flat_inputs = nest.flatten(inputs)
2494 for name, tensor in zip(input_names, flat_inputs):
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| D | base_layer.py | 2639 flat_inputs = nest.flatten((args, kwargs))
2640 input_ids_set = {id(i) for i in flat_inputs}
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| /external/tensorflow/tensorflow/python/tpu/ |
| D | tpu_embedding_v2.py | 936 flat_inputs: List[internal_types.NativeObject],
960 for inp in flat_inputs:
999 flat_inputs, flat_weights, flat_features):
1253 flat_inputs = nest.flatten(features)
1254 flat_weights = [None] * len(flat_inputs)
1279 flat_inputs, flat_weights, flat_features, device_ordinal=-1,
1301 flat_inputs)
1327 flat_inputs, flat_weights, flat_features,
1573 flat_inputs = nest.flatten(inputs)
1574 flat_weights = [None] * len(flat_inputs)
[all …]
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| D | tpu.py | 1292 flat_inputs = []
1294 flat_inputs.append([
1300 flat_input_types = [x.dtype for x in flat_inputs[0]]
1309 types = [x.dtype for x in flat_inputs[i]]
1358 nest.assert_same_structure(flat_inputs[0], flat_maximum_shapes,
1361 unpadded_inputs = flat_inputs
1362 flat_inputs, padding_maps = _pad_all_input(unpadded_inputs,
1378 for i in range(0, len(flat_inputs[0])):
1379 replicas = [flat_inputs[replica][i] for replica in xrange(num_replicas)]
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| /external/tensorflow/tensorflow/python/eager/ |
| D | function.py | 2746 inputs, flat_inputs, filtered_flat_inputs = _convert_numpy_inputs(inputs)
2748 return (inputs, kwargs, flat_inputs + flat_kwargs,
2752 inputs, flat_inputs, filtered_flat_inputs = _convert_inputs_to_signature(
2754 return inputs, {}, flat_inputs, filtered_flat_inputs
2786 flat_inputs = nest.flatten(inputs, expand_composites=True)
2794 for index, value in enumerate(flat_inputs):
2806 flat_inputs[index] = constant_op.constant(a)
2807 filtered_flat_inputs.append(flat_inputs[index])
2811 structure=inputs, flat_sequence=flat_inputs,
2812 expand_composites=True), flat_inputs, filtered_flat_inputs)
[all …]
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| /external/mesa3d/src/compiler/nir/ |
| D | nir_lower_io_to_vector.c | 385 bool flat_inputs[MAX_SLOTS] = {0}; in nir_lower_io_to_vector_impl() local
396 new_inputs, flat_inputs)) in nir_lower_io_to_vector_impl()
449 flat_inputs[loc] : flat_outputs[loc]; in nir_lower_io_to_vector_impl()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | rnn.py | 1337 flat_inputs = nest.flatten(inputs)
1338 for flat_input in flat_inputs:
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| D | control_flow_ops.py | 423 flat_inputs = [nest.flatten(v, expand_composites=True) for v in inputs]
426 for component in zip(*flat_inputs)
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| /external/tensorflow/tensorflow/python/distribute/ |
| D | custom_training_loop_input_test.py | 757 flat_inputs = array_ops.reshape(inputs, [-1])
758 embeddings = array_ops.gather(embedding_weights, flat_inputs)
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| /external/mesa3d/src/intel/blorp/ |
| D | blorp_genX_exec.h | 730 sbe.ConstantInterpolationEnable = prog_data->flat_inputs; in blorp_emit_sf_config()
763 sbe.ConstantInterpolationEnable = prog_data->flat_inputs; in blorp_emit_sf_config()
783 sf.ConstantInterpolationEnable = prog_data->flat_inputs; in blorp_emit_sf_config()
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| /external/mesa3d/src/intel/compiler/ |
| D | brw_compiler.h | 849 uint32_t flat_inputs; member
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| D | brw_fs.cpp | 8552 prog_data->flat_inputs = 0; in brw_compute_flat_inputs()
8564 prog_data->flat_inputs |= 1 << input_index; in brw_compute_flat_inputs()
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| /external/tensorflow/tensorflow/python/keras/ |
| D | backend.py | 6577 flat_inputs = nest.flatten(inputs)
6579 isinstance(i, ragged_tensor.RaggedTensor) for i in flat_inputs)
6587 nested_row_lengths = math_ops.cast(flat_inputs[0].nested_row_lengths()[0],
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| /external/mesa3d/src/mesa/drivers/dri/i965/ |
| D | genX_state_upload.c | 1726 sf.ConstantInterpolationEnable = wm_prog_data->flat_inputs;
3522 sbe.ConstantInterpolationEnable = wm_prog_data->flat_inputs;
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| /external/mesa3d/src/intel/vulkan/ |
| D | genX_pipeline.c | 347 .ConstantInterpolationEnable = wm_prog_data->flat_inputs, in emit_3dstate_sbe()
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| /external/mesa3d/src/gallium/drivers/iris/ |
| D | iris_state.c | 4135 sbe.ConstantInterpolationEnable = wm_prog_data->flat_inputs; in iris_emit_sbe()
|