| /aosp_15_r20/external/pytorch/test/ |
| H A D | test_mkldnn.py | 45 cpu_tensor.requires_grad_()
204 root = torch.randn(4, 5, dtype=torch.float32).to_mkldnn().requires_grad_()
216 root = torch.randn(4, 5, dtype=torch.float32).to_mkldnn().requires_grad_()
256 x1.requires_grad_()
257 x2.requires_grad_()
332 x_ref = x_lower.clone().float().detach().requires_grad_()
333 x_lower.requires_grad_()
384 x1.requires_grad_()
385 x2.requires_grad_()
498 x.requires_grad_()
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| H A D | test_mps.py | 1535 cpu_x.requires_grad_()
1536 mps_x.requires_grad_()
1658 cpu_x = torch.from_numpy(np_features).requires_grad_()
1659 mps_x = torch.from_numpy(np_features).to('mps').requires_grad_()
2084 linear_mps_input = linear_mps_input.requires_grad_()
2085 linear_cpu_input = linear_cpu_input.requires_grad_()
2095 grad = cpu_grad.detach().to('mps').requires_grad_()
2171 high = (torch.ones(5, 5) * 3).requires_grad_()
2173 high_1d = (torch.ones(1) * 3).requires_grad_()
2244 x = cpu_x.detach().clone().to('mps').requires_grad_()
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| H A D | test_nn.py | 149 self.assertIs(m.requires_grad_(requires_grad), m)
1535 m.weight.grad = torch.randn(10, 20).requires_grad_()
1612 m.weight.grad = torch.randn(10, 20).requires_grad_()
1634 m.weight.grad = torch.randn(10, 20).requires_grad_()
1926 m.weight.requires_grad_(requires_grad)
1960 gradcheck(fn, (input.clone().requires_grad_(),), check_batched_grad=False)
2016 gradcheck(fn, (input.clone().requires_grad_(),))
2671 …rch.randn(input_length, batch_size, vocab_size, dtype=torch.double).log_softmax(2).requires_grad_()
2698 inp = torch.randn(T, N, C, dtype=torch.float, device='cuda').log_softmax(2).requires_grad_()
2715 … inp = torch.randn(T, N, C, dtype=torch.float, device=device).log_softmax(2).requires_grad_()
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| H A D | test_expanded_weights.py | 54 weight.clone().requires_grad_(), 3, loss_reduction="sum"
58 bias.clone().requires_grad_(), 3, loss_reduction="sum"
116 weight.clone().requires_grad_(), 4, loss_reduction="sum"
120 bias.clone().requires_grad_(), 4, loss_reduction="sum"
170 input.requires_grad_(False)
182 input.requires_grad_(False)
315 sample_input.input.requires_grad_(False)
630 input.requires_grad_()
696 input.requires_grad_()
1150 res.requires_grad_(t.requires_grad)
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| /aosp_15_r20/external/pytorch/test/distributions/ |
| H A D | test_distributions.py | 178 "concentration1": torch.randn(2, 3).exp().requires_grad_(),
179 "concentration0": torch.randn(2, 3).exp().requires_grad_(),
182 "concentration1": torch.randn(4).exp().requires_grad_(),
183 "concentration0": torch.randn(4).exp().requires_grad_(),
290 {"df": torch.randn(2, 3).exp().requires_grad_()},
291 {"df": torch.randn(1).exp().requires_grad_()},
297 {"df": torch.randn(2, 3).exp().requires_grad_()},
298 {"df": torch.randn(1).exp().requires_grad_()},
304 {"concentration": torch.randn(2, 3).exp().requires_grad_()},
305 {"concentration": torch.randn(4).exp().requires_grad_()},
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| H A D | test_transforms.py | 224 x = generate_data(transform).requires_grad_()
236 x = generate_data(transform).requires_grad_()
338 x = generate_data(transform).requires_grad_()
349 x = generate_data(transform).requires_grad_()
355 y = generate_data(transform.inv).requires_grad_()
366 y = generate_data(transform.inv).requires_grad_()
372 x = generate_data(transform).requires_grad_()
384 x = generate_data(transform).requires_grad_()
566 x = generate_data(transform).requires_grad_()
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| /aosp_15_r20/external/pytorch/torch/testing/_internal/opinfo/definitions/ |
| H A D | sparse.py | 105 return x.detach().clone().requires_grad_(requires_grad)
159 .requires_grad_(requires_grad),
176 inp.requires_grad_(requires_grad),
190 .requires_grad_(requires_grad),
384 .requires_grad_(requires_grad),
390 .requires_grad_(requires_grad),
396 .requires_grad_(requires_grad),
402 .requires_grad_(requires_grad),
408 .requires_grad_(requires_grad),
416 .requires_grad_(requires_grad),
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| /aosp_15_r20/external/pytorch/test/nn/ |
| H A D | test_pooling.py | 223 input = input.contiguous(memory_format=torch.channels_last).requires_grad_()
227 ref_input = input.detach().clone().contiguous().requires_grad_(True)
249 input = input[:, ::2, :, :].requires_grad_()
254 ref_input = input.detach().clone().contiguous().requires_grad_(True)
273 input = input.to(device).to(memory_format=memory_format).requires_grad_()
276 input2 = input.detach().clone().to(dtype=dtype).requires_grad_(True)
319 input = input.contiguous(memory_format=torch.channels_last).requires_grad_()
324 ref_input = input.detach().clone().contiguous().requires_grad_(True)
344 input = input.contiguous(memory_format=torch.channels_last).requires_grad_()
347 ref_input = input.detach().clone().contiguous().requires_grad_(True)
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| H A D | test_convolution.py | 732 i1 = i.data[:, :2].contiguous().requires_grad_(True)
738 i2 = i.data[:, 2:].contiguous().requires_grad_(True)
778 i1 = i.data[:, :2].contiguous().requires_grad_(True)
784 i2 = i.data[:, 2:].contiguous().requires_grad_(True)
816 i1 = i.data[:, :2].contiguous().requires_grad_(True)
822 i2 = i.data[:, 2:].contiguous().requires_grad_(True)
853 i1 = i.data[:, :2].contiguous().requires_grad_(True)
860 i2 = i.data[:, 2:].contiguous().requires_grad_(True)
1143 .requires_grad_(True)
1149 .requires_grad_(True)
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| H A D | test_embedding.py | 355 weight.requires_grad_()
599 weights_check = weights.clone().detach().requires_grad_(True)
718 weights_check = weights.clone().detach().requires_grad_(True)
1014 ).requires_grad_(trainable_scale)
1015 ref_per_sample_weights = per_sample_weights.detach().requires_grad_(
1018 reference_weights = es.weight.detach().requires_grad_()
1078 ).requires_grad_(trainable_scale)
1079 ref_per_sample_weights = per_sample_weights.detach().requires_grad_(
1082 reference_weights = es.weight.detach().requires_grad_()
1154 ).requires_grad_(trainable_scale)
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| /aosp_15_r20/external/pytorch/test/distributed/pipelining/ |
| H A D | test_backward.py | 26 x.requires_grad_(True)
32 ref_x = x.detach().requires_grad_(x.requires_grad)
65 x.requires_grad_(True)
71 ref_x = x.detach().requires_grad_(x.requires_grad)
100 x.requires_grad_(True)
106 ref_x = x.detach().requires_grad_(x.requires_grad)
144 x.requires_grad_(True)
153 ref_inputs.append(x.detach().requires_grad_(x.requires_grad))
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| /aosp_15_r20/external/pytorch/torch/csrc/inductor/aoti_eager/ |
| H A D | kernel_meta_info.cpp | 15 requires_grad_(src_tensor.requires_grad()) {} in TensorMetadata()
31 requires_grad_(requires_grad) { in TensorMetadata()
57 requires_grad_, in build_guard()
84 other.requires_grad_ /* Should we need to care about grad requirement?*/); in operator ==()
90 this->requires_grad_ == other.requires_grad_ && in operator ==()
111 stream << "requires_grad_: " << tensor_metadata.requires_grad_ << '\n'; in operator <<()
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| /aosp_15_r20/external/pytorch/test/inductor/ |
| H A D | test_decompose_mem_bound_mm.py | 89 mat1 = torch.randn(b, m, k, device=GPU_TYPE).requires_grad_(True)
90 mat2 = torch.randn(b, k, n, device=GPU_TYPE).requires_grad_(True)
127 input = torch.randn(m, k, device=GPU_TYPE).requires_grad_(True)
174 input = torch.randn(m, k, device=GPU_TYPE).requires_grad_(True)
218 mat1 = torch.randn(m, k, device=GPU_TYPE).requires_grad_(True)
219 mat2 = torch.randn(k, n, device=GPU_TYPE).requires_grad_(True)
258 mat1 = torch.randn(m, k, device=GPU_TYPE).requires_grad_(True)
259 mat2 = torch.randn(k, n, device=GPU_TYPE).requires_grad_(True)
294 input = torch.randn(m, k, device=GPU_TYPE).requires_grad_(True)
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| /aosp_15_r20/external/pytorch/test/distributed/fsdp/ |
| H A D | test_wrap.py | 75 self.embed_tokens.weight.requires_grad_(False)
76 self.norm.weight.requires_grad_(False)
77 self.norm.bias.requires_grad_(False)
87 self.inp_layernorm.weight.requires_grad_(False)
88 self.inp_layernorm.bias.requires_grad_(False)
89 self.post_attn_layernorm.weight.requires_grad_(False)
90 self.post_attn_layernorm.bias.requires_grad_(False)
102 self.q_proj.weight.requires_grad_(False)
103 self.k_proj.weight.requires_grad_(False)
104 self.v_proj.weight.requires_grad_(False)
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| /aosp_15_r20/external/pytorch/test/dynamo/ |
| H A D | test_aot_autograd_cache.py | 166 a2 = a.detach().clone().requires_grad_(True)
167 b2 = b.detach().clone().requires_grad_(True)
214 a2 = a.detach().clone().requires_grad_(True)
215 b2 = b.detach().clone().requires_grad_(True)
240 a2 = a.detach().clone().requires_grad_(True)
241 b2 = b.detach().clone().requires_grad_(True)
264 a2 = a.detach().clone().requires_grad_(True)
265 b2 = b.detach().clone().requires_grad_(True)
283 a2 = a.detach().clone().requires_grad_(True)
284 b2 = b.detach().clone().requires_grad_(True)
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| /aosp_15_r20/external/pytorch/functorch/examples/maml_regression/ |
| H A D | evjang.py | 30 torch.Tensor(40, 1).uniform_(-1.0, 1.0).requires_grad_(),
31 torch.Tensor(40).zero_().requires_grad_(),
34 .requires_grad_(),
35 torch.Tensor(40).zero_().requires_grad_(),
38 .requires_grad_(),
39 torch.Tensor(1).zero_().requires_grad_(),
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| H A D | evjang_transforms.py | 31 torch.Tensor(40, 1).uniform_(-1.0, 1.0).requires_grad_(),
32 torch.Tensor(40).zero_().requires_grad_(),
35 .requires_grad_(),
36 torch.Tensor(40).zero_().requires_grad_(),
39 .requires_grad_(),
40 torch.Tensor(1).zero_().requires_grad_(),
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| /aosp_15_r20/external/pytorch/test/xpu/ |
| H A D | test_conv.py | 118 out = conv(x.detach().clone().requires_grad_())
154 .requires_grad_()
168 i1 = i.detach()[:, :1].clone().requires_grad_()
175 i2 = i.detach()[:, 1:].clone().requires_grad_()
217 .requires_grad_()
233 i1 = i.detach()[:, :1].clone().requires_grad_()
240 i2 = i.detach()[:, 1:].clone().requires_grad_()
765 w = w.detach().requires_grad_()
954 i1 = i.data[:, :2].contiguous().requires_grad_(True)
961 i2 = i.data[:, 2:].contiguous().requires_grad_(True)
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| /aosp_15_r20/external/pytorch/test/autograd/ |
| H A D | test_complex.py | 11 y = x.detach().requires_grad_(True)
27 y = x.detach().requires_grad_(True)
47 y = x.detach().requires_grad_(True)
78 x.requires_grad_(True)
101 z1 = z.clone().detach().requires_grad_(True)
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| H A D | test_functional.py | 209 return a.long().float().requires_grad_().clone()
235 inp.requires_grad_()
258 inputs.requires_grad_()
259 v.requires_grad_()
333 inputs.requires_grad_()
334 v.requires_grad_()
439 return a.long().float().requires_grad_().clone()
465 inp.requires_grad_()
488 inputs.requires_grad_()
489 v.requires_grad_()
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| /aosp_15_r20/external/pytorch/test/functorch/ |
| H A D | test_aotdispatch.py | 388 x_copy = x.clone().detach().requires_grad_(x.requires_grad)
843 a2 = a.clone().detach().requires_grad_()
844 a3 = a.clone().detach().requires_grad_()
845 a4 = a.clone().detach().requires_grad_()
870 a2 = a.clone().detach().requires_grad_()
871 a3 = a.clone().detach().requires_grad_()
872 a4 = a.clone().detach().requires_grad_()
876 aa2 = aa.clone().detach().requires_grad_()
901 custom_aa_compile = custom_aa.clone().detach().requires_grad_()
926 x2 = x.clone().detach().requires_grad_()
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| /aosp_15_r20/external/pytorch/test/expect/ |
| H A D | TestSparseCPU.test_print_uncoalesced_cpu_float64.expect | 20 # after requires_grad_
52 # after requires_grad_
92 # after requires_grad_
136 # after requires_grad_
176 # after requires_grad_
208 # after requires_grad_
242 # after requires_grad_
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| H A D | TestSparseCPU.test_print_coalesced_cpu_float64.expect | 20 # after requires_grad_
52 # after requires_grad_
92 # after requires_grad_
136 # after requires_grad_
176 # after requires_grad_
208 # after requires_grad_
242 # after requires_grad_
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| H A D | TestSparseCUDA.test_print_coalesced_cuda_float64.expect | 21 # after requires_grad_
57 # after requires_grad_
98 # after requires_grad_
144 # after requires_grad_
188 # after requires_grad_
224 # after requires_grad_
259 # after requires_grad_
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| H A D | TestSparseCUDA.test_print_uncoalesced_cuda_float64.expect | 21 # after requires_grad_
57 # after requires_grad_
98 # after requires_grad_
144 # after requires_grad_
188 # after requires_grad_
224 # after requires_grad_
259 # after requires_grad_
|