| /external/pytorch/test/ |
| D | test_autograd_fallback.py | 142 self.assertEqual(x.grad, torch.ones_like(x))
159 self.assertEqual(x.grad, torch.ones_like(x))
169 self.assertEqual(x.grad, torch.ones_like(x))
243 y, x, torch.ones_like(y), retain_graph=True
247 expected = torch.ones_like(x)
250 (gx,) = torch.autograd.grad(z, x, torch.ones_like(z))
301 torch.autograd.grad(z, y, torch.ones_like(z), allow_unused=True)
310 torch.autograd.grad(z, x, torch.ones_like(z), allow_unused=True)
409 x, (a, b), torch.ones_like(x), allow_unused=True, retain_graph=True
414 y, (a, b), torch.ones_like(y), allow_unused=True, retain_graph=True
[all …]
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| /external/pytorch/test/functorch/ |
| D | test_control_flow.py | 306 grad_out = torch.ones_like(result)
313 grad_out = torch.ones_like(result)
326 ones_like = torch.ops.aten.ones_like.default(getitem, pin_memory = False); getitem = None
329 …ond(pred_1, true_graph_1, false_graph_1, (ones_like, x_1)); pred_1 = true_graph_1 = false_graph_1…
348 grad_out = torch.ones_like(result)
355 grad_out = torch.ones_like(result)
367 ones_like = torch.ops.aten.ones_like.default(getitem, pin_memory = False); getitem = None
370 …ond(pred_1, true_graph_1, false_graph_1, (ones_like, x_1)); pred_1 = true_graph_1 = false_graph_1…
435 grad_out = torch.ones_like(result)
457 grad_out = torch.ones_like(result)
[all …]
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| /external/pytorch/torch/masked/maskedtensor/ |
| D | _ops_refs.py | 368 @register_dispatch_func([torch.ops.aten.ones_like])
369 def ones_like(func, *args, **kwargs): function
418 mx = MaskedTensor(mx, torch.ones_like(mx, dtype=torch.bool))
420 my = MaskedTensor(my, torch.ones_like(my, dtype=torch.bool))
435 mt = MaskedTensor(mt, torch.ones_like(mt, dtype=torch.bool))
452 mt = MaskedTensor(mt, torch.ones_like(mt).bool())
469 mt = MaskedTensor(mt, torch.ones_like(mt).bool())
482 return MaskedTensor(data, torch.ones_like(data).bool())
491 return MaskedTensor(data, torch.ones_like(data).bool())
503 new_args[-1] = torch.ones_like(new_args[-1])
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| /external/tensorflow/tensorflow/python/ops/ |
| D | default_gradient.py | 56 def ones_like(t): function
57 """Like array_ops.ones_like, but respects resource handles."""
61 return array_ops.ones_like(t)
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| D | weights_broadcast_ops.py | 35 (values_shape_2d, array_ops.ones_like(values_shape_2d)), axis=1)
172 weights, array_ops.ones_like(values), name=scope)
175 weights, array_ops.ones_like(values), name=scope)
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| /external/tensorflow/tensorflow/python/eager/ |
| D | tape_test.py | 43 math_ops.matmul(array_ops.ones_like(b * dr), b, transpose_b=True),
45 math_ops.matmul(a, array_ops.ones_like(a) * dr, transpose_b=True)
96 array_ops.ones_like(aa),
110 array_ops.ones_like(aa),
124 array_ops.ones_like(aa),
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| /external/pytorch/test/distributed/_tensor/ |
| D | test_matrix_ops.py | 113 grad_dist_res = torch.ones_like(dist_res)
191 # grad_dist_res = torch.ones_like(dist_res)
217 grad_local_res = torch.ones_like(local_result)
231 grad_local_res = torch.ones_like(local_result)
249 grad_dist_res = torch.ones_like(dist_res)
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| D | test_redistribute.py | 59 grad_output = torch.ones_like(reshard_dtensor)
89 grad_output = torch.ones_like(reshard_replica_tensor)
111 out.backward(torch.ones_like(out))
153 grad_output = torch.ones_like(reshard_tensor)
193 global_partial_tensor.backward(torch.ones_like(global_partial_tensor))
196 self.assertEqual(partial_local.grad, torch.ones_like(partial_local))
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| /external/pytorch/torch/distributions/ |
| D | continuous_bernoulli.py | 106 self._lims[0] * torch.ones_like(self.probs),
116 torch.ge(cut_probs, 0.5), cut_probs, torch.ones_like(cut_probs)
198 torch.where(torch.ge(value, 1.0), torch.ones_like(value), unbounded_cdfs),
232 out_unst_reg, x, (self._lims[0] - 0.5) * torch.ones_like(x)
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| /external/pytorch/torch/csrc/autograd/ |
| D | autograd.cpp | 7 #include <ATen/ops/ones_like.h>
44 at::ones_like(output, LEGACY_CONTIGUOUS_MEMORY_FORMAT)); in _make_grads()
68 at::ones_like(output, LEGACY_CONTIGUOUS_MEMORY_FORMAT)); in _make_grads()
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| /external/pytorch/test/nn/ |
| D | test_pruning.py | 169 self.assertEqual(old_grad_weight, torch.ones_like(m.weight))
171 self.assertEqual(old_grad_bias, torch.ones_like(m.bias))
202 self.assertEqual(old_grad_weight, torch.ones_like(m.weight))
204 self.assertEqual(old_grad_bias, torch.ones_like(m.bias))
213 compute_mask.return_value = torch.ones_like(m.weight)
237 mask = torch.ones_like(m.weight)
252 self.assertEqual(m.bias.grad, torch.ones_like(m.bias))
292 mask = torch.ones_like(m.weight)
510 computed_mask = p.compute_mask(t, default_mask=torch.ones_like(t))
521 computed_mask = p.compute_mask(t, default_mask=torch.ones_like(t))
[all …]
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| /external/libopus/dnn/torch/dnntools/dnntools/sparsification/ |
| D | utils.py | 43 count = torch.ones_like(p).sum().item()
57 num_zero_parameters = torch.ones_like(module.weight).sum().item() * (1 - params[0])
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| /external/tensorflow/tensorflow/python/eager/benchmarks/resnet50/ |
| D | hvp_test.py | 57 helpers = tf.nest.map_structure(tf.ones_like, grads)
91 vector = [tf.ones_like(v) for v in model.trainable_variables]
123 vector = [tf.ones_like(v) for v in model.trainable_variables]
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| /external/tensorflow/tensorflow/core/transforms/constant_folding/tests/ |
| D | materialize_constant_value_node.mlir | 7 …// CHECK-DAG: Const [%[[CTRL]]] name("ones_like") {{.*}} value = dense<1.000000e+00> {{.*}} -> (te…
8 …%OnesLike, %ctl_0 = OnesLike(%Placeholder) name("ones_like") {T = f32} : (tensor<1x2x3x4xf32>) -> …
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | multinomial.py | 247 n_draws = array_ops.ones_like(
249 logits = array_ops.ones_like(
291 p = self.probs * array_ops.ones_like(
301 p = self.probs * array_ops.ones_like(
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| D | normal.py | 219 scale = self.scale * array_ops.ones_like(self.loc)
223 return self.loc * array_ops.ones_like(self.scale)
229 return self.scale * array_ops.ones_like(self.loc)
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| /external/executorch/examples/models/llama/source_transformation/ |
| D | apply_spin_quant_r1_r2.py | 184 layer.ffn_norm.weight.data = torch.ones_like(W_norm, dtype=torch.float32)
186 layer.attention_norm.weight.data = torch.ones_like(W_norm, dtype=torch.float32)
199 model.norm.weight.data = torch.ones_like(W_norm, dtype=torch.float32)
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| /external/pytorch/torch/ao/pruning/_experimental/activation_sparsifier/ |
| D | README.md | 57 mask = torch.ones_like(tensor)
85 mask = torch.ones_like(tensor)
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| /external/pytorch/torch/distributed/_shard/sharded_tensor/_ops/ |
| D | init.py | 119 torch.ones_like: sharded_tensor.ones,
149 register_tensor_creation_op(torch.ones_like)
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| /external/pytorch/test/mobile/lightweight_dispatch/ |
| D | tests_setup.py | 103 # ones_like(Tensor self, *, ScalarType?, dtype=None, Layout? layout=None, Device? device=None, bool…
108 b = torch.ones_like(a)
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| /external/pytorch/test/typing/pass/ |
| D | creation_ops.py | 55 # torch.ones/ones_like
60 torch.ones_like(torch.empty(2, 3))
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| /external/tensorflow/tensorflow/python/tpu/ |
| D | tpu_embedding_v1.py | 330 array_ops.ones_like(inp.values, dtype=dtypes.float32),
383 array_ops.ones_like(inp.values, dtype=dtypes.float32),
388 weight = array_ops.ones_like(inp, dtype=dtypes.float32)
406 weight = array_ops.ones_like(inp, dtype=dtypes.float32)
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| /external/pytorch/test/distributed/tensor/parallel/ |
| D | test_tp_style.py | 376 grad_out = torch.ones_like(sharded_out)
399 grad_out = torch.ones_like(sharded_out)
417 grad_out = torch.ones_like(sharded_out)
430 grad_out = torch.ones_like(sharded_out)
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| /external/pytorch/torch/csrc/jit/passes/ |
| D | frozen_linear_folding.cpp | 11 #include <ATen/ops/ones_like.h>
94 bn_w = at::ones_like(bn_rm); in FoldFrozenLinearBatchnorm()
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| /external/libopus/dnn/torch/osce/utils/ |
| D | moc.py | 14 vactive = np.ones_like(frames)
125 mask = np.ones_like(Ef)
|