/aosp_15_r20/external/pytorch/aten/src/ATen/native/vulkan/ops/ |
H A D | Clamp.cpp | 187 Tensor& clamp_( in clamp_() function 191 return _clamp_(self, min, max, VK_KERNEL(clamp_)); in clamp_() 291 return ops::_clamp_(self, min, max, VK_KERNEL(clamp_)); in hardtanh_() 313 : ops::_clamp_(self, 0, std::nullopt, VK_KERNEL(clamp_)))); in relu_() 598 m.impl(TORCH_SELECTIVE_NAME("aten::clamp_"), TORCH_FN(clamp_)); in TORCH_LIBRARY_IMPL()
|
/aosp_15_r20/external/OpenCL-CTS/test_conformance/commonfns/ |
H A D | test_clamp.cpp | 34 const char *clamp_##type##_kernel_code = EMIT_PRAGMA_DIRECTIVE \ 44 const char *clamp_##type##size##_kernel_code = EMIT_PRAGMA_DIRECTIVE \ 55 const char *clamp_##type##size##_kernel_code = EMIT_PRAGMA_DIRECTIVE \
|
/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/quantization/ |
H A D | helper.cpp | 160 // "clamp_", // Enable when quantized `clamp_` is ready 171 // "clamp_", // Enable when quantized `clamp_` is ready
|
/aosp_15_r20/external/pytorch/torch/distributions/ |
H A D | fishersnedecor.py | 87 X2.clamp_(min=tiny) 89 Y.clamp_(min=tiny)
|
H A D | gamma.py | 77 value.detach().clamp_(
|
/aosp_15_r20/external/pytorch/torch/ao/quantization/ |
H A D | _learnable_fake_quantize.py | 150 self.scale.data.clamp_(min=self.eps.item()) # type: ignore[operator] 169 self.scale.data.clamp_(min=self.eps.item()) # type: ignore[operator]
|
/aosp_15_r20/external/pytorch/test/expect/ |
H A D | HasDecompTest.test_aten_core_operators.expect | 144 aten::clamp_ 145 aten::clamp_.Tensor
|
/aosp_15_r20/external/pytorch/torch/optim/ |
H A D | rprop.py | 275 step_size.mul_(sign).clamp_(step_size_min, step_size_max) 380 step_size.clamp_(step_size_min, step_size_max)
|
H A D | _adafactor.py | 395 var_estimate.div_(row_var.mean(dim=-2, keepdim=True).clamp_(min=eps1)) 406 update = var_estimate.clamp_(min=eps1 * eps1).rsqrt_()
|
/aosp_15_r20/external/pytorch/test/ |
H A D | test_shape_ops.py | 324 torch.Tensor.clamp_, 357 torch.Tensor.clamp_, 397 X.clamp_()
|
H A D | test_numba_integration.py | 71 indices_t = torch.empty(1, cput.size(0), dtype=torch.long).clamp_(min=0)
|
/aosp_15_r20/external/coreboot/src/commonlib/bsd/include/commonlib/bsd/ |
H A D | clamp.h | 12 static inline type clamp_##type(const type min, const type val, const type max) \
|
/aosp_15_r20/external/pytorch/torch/testing/_internal/ |
H A D | common_nn.py | 196 input_fn=lambda: torch.rand(15, 10).clamp_(2.8e-2, 1 - 2.8e-2), 212 input_fn=lambda: torch.rand(()).clamp_(2.8e-2, 1 - 2.8e-2), 230 input_fn=lambda: torch.rand(15, 10).clamp_(2.8e-2, 1 - 2.8e-2), 251 input_fn=lambda: torch.rand(()).clamp_(2.8e-2, 1 - 2.8e-2), 267 input_fn=lambda: torch.rand(15, 10).clamp_(2.8e-2, 1 - 2.8e-2), 285 input_fn=lambda: torch.rand(15, 10).clamp_(2.8e-2, 1 - 2.8e-2), 303 input_fn=lambda: torch.rand(()).clamp_(2.8e-2, 1 - 2.8e-2), 1010 input_fn=lambda: torch.randn(5, 10).clamp_(1e-2, 1 - 1e-2),
|
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/utils/ |
H A D | clip_grad.h | 125 param.grad().data().clamp_(-clip_value, clip_value); in clip_grad_value_()
|
/aosp_15_r20/external/pytorch/test/mobile/model_test/ |
H A D | coverage.yaml | 132 - aten::clamp_ 770 aten::clamp_: 12
|
H A D | tensor_ops.py | 81 a.clamp_(0),
|
H A D | model_ops.yaml | 91 aten::clamp_: 19
|
/aosp_15_r20/external/pytorch/torch/nn/utils/ |
H A D | clip_grad.py | 189 cast(Tensor, grad).clamp_(min=-clip_value, max=clip_value)
|
/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/ |
H A D | normalize_ops.cpp | 87 {aten::clip_, aten::clamp_}, in getOperatorAliasMap()
|
/aosp_15_r20/external/pytorch/aten/src/ATen/core/ |
H A D | NamedRegistrations.cpp | 104 m.impl("clamp_", CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL() 105 m.impl("clamp_.Tensor", CppFunction::makeFallthrough()); in TORCH_LIBRARY_IMPL()
|
/aosp_15_r20/external/pytorch/aten/src/ATen/native/ |
H A D | TensorCompare.cpp | 774 return at::clamp_(self, min, max); in clip_() 778 return at::clamp_(self, min, max); in clip_()
|
/aosp_15_r20/external/pytorch/aten/src/ATen/native/quantized/ |
H A D | FakeQuantPerChannelAffine.cpp | 138 return zero_point.round().clamp_(quant_min, quant_max); in _get_rounded_zero_point()
|
/aosp_15_r20/external/pytorch/test/cpp_api_parity/ |
H A D | utils.py | 291 # input_fn=lambda: torch.rand(15, 10).clamp_(2.8e-2, 1 - 2.8e-2),
|
/aosp_15_r20/external/pytorch/torch/testing/_internal/opinfo/ |
H A D | core.py | 2319 a.real.clamp_(low, high) 2320 a.imag.clamp_(low, high) 2322 a.clamp_(min=low, max=high)
|
/aosp_15_r20/external/pytorch/torch/distributed/tensor/_ops/ |
H A D | _pointwise_ops.py | 148 aten.clamp_.default,
|