Searched refs:all_tensors (Results 1 – 16 of 16) sorted by relevance
| /external/tensorflow/tensorflow/lite/testing/op_tests/ |
| D | pack.py | 72 all_tensors = []
78 all_tensors.append(input_tensor)
79 out = tf.stack(all_tensors, parameters["axis"])
80 return all_tensors, [out]
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| D | concat.py | 79 all_tensors = []
85 all_tensors.append(input_tensor)
86 out = tf.concat(all_tensors, parameters["axis"])
87 return all_tensors, [out]
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| /external/pytorch/torch/testing/_internal/optests/ |
| D | autograd_registration.py | 76 all_tensors = [arg for arg in flat_args if isinstance(arg, torch.Tensor)]
77 if not any(t.requires_grad for t in all_tensors):
85 all_device_types = {arg.device.type for arg in all_tensors}
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| /external/tensorflow/tensorflow/python/ops/ |
| D | custom_gradient.py | 485 all_tensors = flat_result + args + variables
510 original_tensors = all_tensors
512 all_tensors = array_ops.identity_n(all_tensors)
519 all_tensors[i]._handle_data = t._handle_data # pylint: disable=protected-access
521 f.__name__, all_tensors, original_tensors, tape_grad_fn)
522 for ot, t in zip(original_tensors, all_tensors):
525 structure=result, flat_sequence=all_tensors[:flat_result_len])
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| D | math_ops.py | 219 all_tensors = (expanded_start, res, expanded_stop)
220 concatenated = array_ops.concat(all_tensors, axis=axis)
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| /external/tensorflow/tensorflow/python/tools/ |
| D | inspect_checkpoint.py | 54 def print_tensors_in_checkpoint_file(file_name, tensor_name, all_tensors, argument
73 if all_tensors or all_tensor_names:
78 if all_tensors:
159 FLAGS.all_tensors, FLAGS.all_tensor_names,
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| /external/pytorch/test/fx/ |
| D | quantization.py | 40 self.all_tensors = True
45 self.all_tensors = False
76 if not self.all_tensors:
208 assert self.all_tensors
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| /external/pytorch/torch/testing/_internal/ |
| D | jit_metaprogramming_utils.py | 406 all_tensors: List[Any]
426 self.all_tensors = [*self.tensor_args, *[v for k, v in self.tensor_kwargs.items()]]
464 traced = torch.jit.trace(fn_tensors, split_inputs.all_tensors, check_trace=False)
465 self.assertExportImport(traced.graph, split_inputs.all_tensors)
466 output = traced(*split_inputs.all_tensors)
473 output = traced_fn.traced(*split_inputs.all_tensors)
476 … traced_fn.last_graph = traced.graph_for(*split_inputs.all_tensors) # type: ignore[attr-defined]
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| D | composite_compliance.py | 254 all_tensors = all(isinstance(elt, torch.Tensor) for elt in lst)
255 if all_tensors:
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| /external/tensorflow/tensorflow/python/eager/ |
| D | gradient_input_output_exclusions.py | 315 all_tensors = set(range(num_values))
316 unused_tensors = all_tensors - used_tensors
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| /external/pytorch/torch/utils/model_dump/ |
| D | code.js | 537 let all_tensors = [];
540 all_tensors.push(...tensors.values());
543 for (const storage of all_tensors.values()) {
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| /external/tensorflow/tensorflow/python/training/ |
| D | saver.py | 169 all_tensors = []
176 all_tensors.extend(
178 return all_tensors
360 all_tensors = self.bulk_restore(filename_tensor, saveables, preferred_shard,
381 saveable_tensors = all_tensors[idx:idx + len(saveable.specs)]
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| /external/ComputeLibrary/src/dynamic_fusion/sketch/utils/ |
| D | DependencyGraph.h | 280 std::vector<TensorId> all_tensors() const in all_tensors() function
467 for(auto t : all_tensors()) in remove_operator()
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| /external/pytorch/torch/distributed/optim/ |
| D | zero_redundancy_optimizer.py | 1415 all_tensors = True
1418 all_tensors &= isinstance(param, torch.Tensor)
1420 if not all_tensors and not all_dicts:
1425 if all_tensors:
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| /external/pytorch/torch/distributed/fsdp/ |
| D | _optim_utils.py | 1009 all_tensors = True
1012 all_tensors &= isinstance(param, torch.Tensor)
1014 if not all_tensors and not all_dicts:
1016 if all_tensors:
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| /external/pytorch/torch/onnx/ |
| D | symbolic_opset9.py | 6229 all_tensors = symbolic_helper._unpack_list(self)
6230 t_with_final_shape = zeros_like(g, all_tensors[0])
6234 for t in all_tensors:
6237 t_list = [expand_as(g, t, t_with_final_shape) for t in all_tensors]
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