| /external/pytorch/torch/csrc/jit/runtime/ |
| D | serialized_shape_function_registry.cpp | 940 _0 = "AssertionError: max_pool2d: kernel_size must either be a single int, or a tuple of two ints"
941 …_1 = "AssertionError: max_pool2d: stride must either be omitted, a single int, or a tuple of two i…
942 _2 = "AssertionError: max_pool2d: padding must either be a single int, or a tuple of two ints"
943 _3 = "AssertionError: max_pool2d: dilation must be either a single int, or a tuple of two ints"
1153 _0 = "AssertionError: max_pool2d: kernel_size must either be a single int, or a tuple of two ints"
1154 …_1 = "AssertionError: max_pool2d: stride must either be omitted, a single int, or a tuple of two i…
1155 _2 = "AssertionError: max_pool2d: padding must either be a single int, or a tuple of two ints"
1156 _3 = "AssertionError: max_pool2d: dilation must be either a single int, or a tuple of two ints"
|
| /external/pytorch/test/onnx/model_defs/ |
| D | mnist.py | 15 x = F.relu(F.max_pool2d(self.conv1(x), 2))
16 x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
|
| /external/executorch/backends/arm/quantizer/quantization_annotation/ |
| D | max_pool2d_annotator.py | 31 gm.graph, [torch.nn.MaxPool2d, torch.nn.functional.max_pool2d], filter_fn
40 if n.target == torch.ops.aten.max_pool2d.default:
|
| /external/pytorch/torch/_inductor/ |
| D | quantized_lowerings.py | 34 quantized.max_pool2d,
40 lowering.make_fallback(quantized.max_pool2d)
|
| /external/pytorch/aten/src/ATen/native/metal/ops/ |
| D | MetalPooling.mm | 17 static Tensor max_pool2d(
105 m.impl(TORCH_SELECTIVE_NAME("aten::max_pool2d"), TORCH_FN(max_pool2d));
|
| /external/pytorch/test/cpp/api/ |
| D | integration.cpp | 265 x = torch::max_pool2d(conv1->forward(x), {2, 2}).relu(); in TEST_F()
268 x = torch::max_pool2d(x, {2, 2}).relu(); in TEST_F()
301 x = torch::max_pool2d(conv1->forward(x), {2, 2}).relu(); in TEST_F()
304 x = torch::max_pool2d(x, {2, 2}).relu(); in TEST_F()
|
| /external/pytorch/benchmarks/tensorexpr/ |
| D | pt_engine.py | 66 def max_pool2d(self, data, kernel_size, stride=1): member in TorchTensorEngine
67 return torch.nn.functional.max_pool2d(data, kernel_size, stride=stride)
|
| D | pooling.py | 19 y = self.max_pool2d(self.data, self.kernel_size, stride=1)
|
| /external/executorch/docs/source/tutorials_source/ |
| D | devtools-integration-tutorial.py | 80 x = F.max_pool2d(F.relu(self.conv1(x)), (2, 2))
82 x = F.max_pool2d(F.relu(self.conv2(x)), 2)
|
| /external/pytorch/aten/src/ATen/native/ |
| D | Pooling.cpp | 140 Tensor max_pool2d( in max_pool2d() function
158 return xnnpack::max_pool2d( in max_pool2d()
|
| /external/pytorch/aten/src/ATen/native/vulkan/ops/ |
| D | Pool.cpp | 246 Tensor max_pool2d( in max_pool2d() function
279 VK_KERNEL(max_pool2d)); in max_pool2d()
290 m.impl(TORCH_SELECTIVE_NAME("aten::max_pool2d"), TORCH_FN(max_pool2d)); in TORCH_LIBRARY_IMPL()
|
| /external/tensorflow/tensorflow/python/layers/ |
| D | pooling.py | 38 max_pool2d = max_pooling2d variable
|
| /external/pytorch/aten/src/ATen/native/xnnpack/ |
| D | Shim.cpp | 80 Tensor max_pool2d( in max_pool2d() function
|
| D | Engine.h | 59 Tensor max_pool2d(
|
| /external/executorch/backends/vulkan/runtime/graph/ops/impl/ |
| D | Pool.cpp | 116 void max_pool2d(ComputeGraph& graph, const std::vector<ValueRef>& args) { in max_pool2d() function
207 VK_REGISTER_OP(aten.max_pool2d_with_indices.default, max_pool2d);
|
| /external/pytorch/torch/csrc/jit/codegen/onednn/ |
| D | register_interface.cpp | 27 case aten::max_pool2d: in canFuseNode()
|
| /external/executorch/backends/xnnpack/_passes/ |
| D | remove_getitem_op.py | 65 exir_ops.edge.aten.max_pool2d.default,
|
| /external/pytorch/torch/ao/pruning/_experimental/pruner/ |
| D | base_structured_sparsifier.py | 152 F.max_pool2d,
176 F.max_pool2d,
|
| /external/pytorch/functorch/notebooks/_src/ |
| D | plot_ensembling.py | 41 x = F.max_pool2d(x, 2)
|
| D | plot_per_sample_gradients.py | 34 x = F.max_pool2d(x, 2)
|
| /external/pytorch/torch/csrc/api/include/torch/nn/functional/ |
| D | pooling.h | 223 inline Tensor max_pool2d( in max_pool2d() function
230 return torch::max_pool2d( in max_pool2d()
248 inline Tensor max_pool2d( in max_pool2d() function
251 return detail::max_pool2d( in max_pool2d()
|
| /external/pytorch/torch/ao/nn/quantized/ |
| D | functional.py | 508 def max_pool2d( function
528 return torch.nn.functional.max_pool2d(
|
| /external/pytorch/torch/csrc/lazy/ |
| D | test_mnist.py | 35 x = F.max_pool2d(x, 2)
|
| /external/pytorch/docs/source/ |
| D | nn.functional.rst | 36 max_pool2d
|
| /external/pytorch/torch/onnx/ |
| D | symbolic_caffe2.py | 230 def max_pool2d( function
240 return opset9.max_pool2d( # type: ignore[attr-defined]
|