| /external/executorch/backends/qualcomm/_passes/ |
| D | recompose_rms_norm.py | 29 def _get_gamma_node(self, output_node): argument
31 for a in output_node.args:
51 output_node = src_partition.output_nodes[0]
53 gamma_node = self._get_gamma_node(output_node)
55 with graph.inserting_before(output_node):
68 users = output_node.users.copy()
70 user.replace_input_with(output_node, rms_node)
72 rms_node.meta = output_node.meta
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| D | convert_interpolate_with_upsample2d.py | 28 output_node = src_partition.output_nodes[0]
32 if output_node.target.__name__ == "aten.index.Tensor":
35 output_size = list(output_node.meta["val"].shape)
41 output_size = list(output_node.meta["val"].shape)
48 users = output_node.users.copy()
50 user.replace_input_with(output_node, upsample2d_node)
52 upsample2d_node.meta = output_node.meta
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| D | convert_prelu.py | 27 output_node = src_partition.output_nodes[0]
36 users = output_node.users.copy()
38 user.replace_input_with(output_node, prelu_node)
40 prelu_node.meta = output_node.meta
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| D | fuse_consecutive_transpose.py | 53 input_node, output_node = self.nodes[0].args[0], self.nodes[-1]
64 users = output_node.users.copy()
66 user.replace_input_with(output_node, permute_node)
69 permute_node.meta = output_node.meta
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| /external/pytorch/torch/_export/passes/ |
| D | replace_with_hop_pass_util.py | 43 output_node = next(iter(reversed(sub_gm.graph.nodes)), None)
48 if isinstance(output_node, torch.fx.Node) and output_node.op != "output":
49 output_node = None
50 if output_node is not None:
51 assert len(output_node.args) == 1
52 output_args = output_node.args[0]
68 output_node = output_args[idx]
69 get_item_node._rename(output_node.name)
70 get_item_node.meta = output_node.meta
81 output_node.args = ((output_args,),)
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| /external/executorch/exir/passes/ |
| D | weights_to_outputs_pass.py | 49 output_node = None
52 output_node = node
54 assert output_node is not None
71 new_output_nodes.extend(output_node.args[0])
75 output_node.replace_all_uses_with(new_output)
76 gm.graph.erase_node(output_node)
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| D | insert_write_back_for_buffers_pass.py | 31 output_node = None
34 output_node = node
36 assert output_node is not None
37 outputs = pytree.tree_flatten(output_node.args)[0]
57 with gm.graph.inserting_before(output_node):
64 with gm.graph.inserting_before(output_node):
68 output_node.replace_all_uses_with(new_output)
69 gm.graph.erase_node(output_node)
|
| /external/tensorflow/tensorflow/python/tools/ |
| D | strip_unused_test.py | 45 output_node = math_ops.multiply(
47 math_ops.add(output_node, 2.0, name="later_node")
49 output = self.evaluate(output_node)
94 output_node = sess.graph.get_tensor_by_name("output_node:0")
95 output = sess.run(output_node, feed_dict={input_node: [10.0]})
108 output_node = math_ops.multiply(
110 math_ops.add(output_node, 2.0, name="later_node")
112 output = self.evaluate(output_node)
152 output_node = sess.graph.get_tensor_by_name("output_node:0")
153 output = sess.run(output_node,
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| D | freeze_graph_test.py | 60 output_node = math_ops.multiply(variable_node, 2.0, name="output_node")
64 output = sess.run(output_node)
114 output_node = sess.graph.get_tensor_by_name("output_node:0")
115 output = sess.run(output_node)
176 output_node = math_ops.multiply(variable_node, 2.0, name="output_node")
180 output = sess.run(output_node)
216 output_node = sess.graph.get_tensor_by_name("output_node:0")
217 output = sess.run(output_node)
270 output_node = sess.graph.get_tensor_by_name("output_node:0")
271 output = sess.run(output_node, feed_dict={input_node: [example]})
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| /external/executorch/backends/xnnpack/operators/ |
| D | op_multiply.py | 61 output_node = get_relu_fused_node(node) or node
64 if output_node.target == exir_ops.edge.aten.relu.default:
65 output_node.meta["XNNPACK_FUSED"] = True
69 output_node,
72 quant_params=QuantParams.from_outputs(output_node),
75 output_id = vals_to_ids[output_node]
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| /external/executorch/exir/emit/ |
| D | _emit_program.py | 53 output_node = None
56 output_node = node
57 assert output_node is not None
63 outputs = pytree.tree_flatten(output_node.args)[0]
71 with gm.graph.inserting_before(output_node):
74 new_output.meta = output_node.meta.copy()
75 output_node.replace_all_uses_with(new_output)
76 gm.graph.erase_node(output_node)
|
| /external/tensorflow/tensorflow/core/data/ |
| D | rewrite_utils.cc | 105 const std::string& output_node = tensor.substr(0, tensor.find(':')); in RemoveFakeSinks() local
106 if (identity_map.find(output_node) != identity_map.end()) { in RemoveFakeSinks()
108 identity_map.at(output_node); in RemoveFakeSinks()
176 string output_node; in RewriteDataset() local
178 AsGraphDefForRewrite(ctx, input, &input_list, &graph_def, &output_node)); in RewriteDataset()
182 ApplyRewrites(ctx, config_factory, &graph_def, &output_node)); in RewriteDataset()
203 graph_runner.Run(&graph, flr, input_list, {output_node}, &outputs)); in RewriteDataset()
214 output_node = std::move(output_node)]() { in RewriteDataset()
218 if (node.name() == output_node) { in RewriteDataset()
224 VLOG(3) << "Failed to find node: " << output_node; in RewriteDataset()
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| D | serialization_utils.cc | 59 const string& output_node, Tensor* result) { in FromGraphDef() argument
70 {output_node}, &outputs)); in FromGraphDef()
278 tstring output_node, serialized_graph_def; in ReadDatasetInternal() local
280 ReadScalar(n, strings::StrCat(key, kOutputNode), &output_node)); in ReadDatasetInternal()
285 TF_RETURN_IF_ERROR(FromGraphDef(flr, graph_def, {}, output_node, val)); in ReadDatasetInternal()
404 string output_node; in WriteDatasetInternal() local
407 output_node = node.input(0); in WriteDatasetInternal()
415 WriteScalar(n, strings::StrCat(key, kOutputNode), output_node)); in WriteDatasetInternal()
461 Node* output_node = nullptr; in AsGraphDef() local
463 db.AddInputDataset(&serialization_ctx, dataset, &output_node)); in AsGraphDef()
[all …]
|
| /external/executorch/exir/tests/ |
| D | test_joint_graph.py | 44 output_node = None
47 output_node = node
50 orig_outputs = len(output_node.args[0])
60 output_node = None
63 output_node = node
66 weight_outputs = len(output_node.args[0])
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| /external/autotest/client/site_tests/audio_Aplay/ |
| D | audio_Aplay.py | 132 output_node = audio_spec.get_headphone_node(utils.get_board())
135 output_node = "INTERNAL_SPEAKER"
139 logging.debug("Test output device %s", output_node)
141 cras_utils.set_single_selected_output_node(output_node)
145 if cras_device_type != output_node:
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| /external/tensorflow/tensorflow/core/graph/ |
| D | benchmark_testlib.h | 168 NodeDef output_node = create_node(/*name=*/absl::StrFormat("out%05d", i)); in CreateFaninFanoutNodeGraph() local
171 output_node.add_input(input_node_index); in CreateFaninFanoutNodeGraph()
172 *graph.add_node() = std::move(output_node); in CreateFaninFanoutNodeGraph()
177 NodeDef output_node = in CreateFaninFanoutNodeGraph() local
179 output_node.add_input(controlled_fanout_input); in CreateFaninFanoutNodeGraph()
180 *graph.add_node() = std::move(output_node); in CreateFaninFanoutNodeGraph()
|
| /external/pytorch/torch/_inductor/codegen/rocm/ |
| D | rocm_template.py | 44 self.output_node: Buffer = Buffer("buf_out", layout)
65 V.graph, "get_dtype", self._fake_get_dtype(self.output_node)
86 expected_args.extend([self.output_node.get_name()])
101 output_tensor_meta=TensorMeta.from_irnodes(self.output_node),
126 self.output_node.get_layout(),
|
| /external/pytorch/torch/export/ |
| D | _unlift.py | 80 output_node = None
83 output_node = node
85 assert output_node is not None
86 outputs = pytree.tree_flatten(output_node.args)[0]
105 with gm.graph.inserting_before(output_node):
115 with gm.graph.inserting_before(output_node):
118 new_output.meta.update(output_node.meta)
119 output_node.replace_all_uses_with(new_output)
120 gm.graph.erase_node(output_node)
|
| D | _remove_effect_tokens_pass.py | 24 output_node = None
29 output_node = next(reversed(ep.graph_module.graph.find_nodes(op="output")))
41 assert output_node is not None
42 output_args = output_node.args[0]
45 output_node.args = (tuple(output_args[num_tokens:]),)
|
| /external/pytorch/torch/_inductor/codegen/ |
| D | cpp_template.py | 36 self.output_node: ir.Buffer = ir.Buffer("buf_out", layout)
44 V.graph, "get_dtype", self._fake_get_dtype(self.output_node)
60 expected_args.extend([self.output_node.get_name()])
78 output_tensor_meta=TensorMeta.from_irnodes(self.output_node),
105 self.output_node.get_layout(),
|
| /external/pytorch/torch/_inductor/codegen/cuda/ |
| D | cuda_template.py | 46 self.output_node: Buffer = Buffer("buf_out", layout)
66 V.graph, "get_dtype", self._fake_get_dtype(self.output_node)
87 expected_args.extend([self.output_node.get_name()])
102 output_tensor_meta=TensorMeta.from_irnodes(self.output_node),
127 self.output_node.get_layout(),
|
| /external/pytorch/torch/fx/passes/ |
| D | split_utils.py | 157 output_node: Optional[torch.fx.Node] = None
168 if output_node is not None:
170 output_node = node
236 if output_node is None:
239 for x in flatten(output_node.args[0]):
289 main_g.output(map_arg(output_node.args[0], main_remapping.__getitem__))
295 for x in flatten(output_node.args[0]):
|
| /external/executorch/backends/cadence/aot/ |
| D | compiler_utils.py | 22 output_node = next(iter(reversed(graph.nodes)))
24 output_node and output_node.op == "output" and len(output_node.args) == 1
26 return output_node
31 output_node = get_output_node(graph)
32 return node in tree_flatten(output_node.args[0])[0]
|
| /external/executorch/backends/arm/quantizer/quantization_annotation/ |
| D | max_pool2d_annotator.py | 37 output_node = maxpool_partition.output_nodes[0]
46 … if arm_quantizer_utils.are_annotated([output_node, maxpool_node]): # type: ignore[list-item]
68 output_node.meta["quantization_annotation"] = QuantizationAnnotation(
|
| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/ |
| D | feed-control-dep.pbtxt | 1 …-tf-input-arrays=input -tf-input-data-types=DT_FLOAT -tf-output-arrays=output_node -o - | FileChec…
46 name: "output_node"
66 # CHECK-SAME: outputs = "output_node"
|