Home
last modified time | relevance | path

Searched full:log_probs (Results 1 – 25 of 27) sorted by relevance

12

/aosp_15_r20/external/pytorch/aten/src/ATen/native/
H A DLossCTC.cpp7 // Graves et al. call the probabilities y, we use log_probs (also calling them inputs)
56 …, size_t, std::vector<int64_t>> ctc_loss_allocate_outputs(const Tensor& log_probs, const Tensor& t… in ctc_loss_allocate_outputs() argument
57 // log_probs: input_len x batch_size x num_labels in ctc_loss_allocate_outputs()
61 auto log_probs_arg = TensorArg(log_probs, "log_probs", 1); in ctc_loss_allocate_outputs()
67 int64_t batch_size = log_probs.size(1); in ctc_loss_allocate_outputs()
68 int64_t num_labels = log_probs.size(2); in ctc_loss_allocate_outputs()
108 int64_t max_input_length = log_probs.size(0); in ctc_loss_allocate_outputs()
118 …Tensor log_alpha = at::empty({batch_size, log_probs.size(0), 2*max_target_length+1}, log_probs.opt… in ctc_loss_allocate_outputs()
119 Tensor neg_log_likelihood = at::empty({batch_size}, log_probs.options()); in ctc_loss_allocate_outputs()
125 // A (minor) twist is that we are using log-calculations to enhance numerical stability (log_probs …
[all …]
H A Dnative_functions.yaml219 - func: _use_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_len…
224 - func: _use_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor t…
229 - func: _cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths…
230 …device_check: NoCheck # log_probs is expected to be on CUDA while targets is expected to be on CPU
235 - func: _cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor targe…
236 …device_check: NoCheck # log_probs is expected to be on CUDA while targets is expected to be on CPU
2028 - func: ctc_loss.IntList(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_length…
2031 - func: ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengt…
2033 - func: _ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int …
2041 - func: _ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_leng…
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/cudnn/
H A DLossCTC.cpp30 const Tensor& log_probs, in _use_cudnn_ctc_loss() argument
39 const Tensor& log_probs, in _use_cudnn_ctc_loss_tensor() argument
48 const Tensor& log_probs, in _cudnn_ctc_loss() argument
59 const Tensor& log_probs, in _cudnn_ctc_loss_tensor() argument
90 const Tensor& log_probs, in _use_cudnn_ctc_loss() argument
98 (targets.dim() == 1) && (log_probs.scalar_type() == at::kFloat) && in _use_cudnn_ctc_loss()
101 (log_probs.device().type() == at::kCUDA) && (log_probs.dim() == 3); in _use_cudnn_ctc_loss()
106 int64_t max_input_length = log_probs.size(0); in _use_cudnn_ctc_loss()
121 const Tensor& log_probs, in _use_cudnn_ctc_loss_tensor() argument
129 (targets.dim() == 1) && (log_probs.scalar_type() == at::kFloat) && in _use_cudnn_ctc_loss_tensor()
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/cuda/
H A DLossCTC.cu7 // Graves et al. call the probabilities y, we use log_probs (also calling them inputs)
65 // A (minor) twist is that we are using log-calculations to enhance numerical stability (log_probs …
221 std::tuple<Tensor, Tensor> ctc_loss_gpu_template(const Tensor& log_probs, const Tensor& targets, In… in ctc_loss_gpu_template() argument
222 // log_probs: input_len x batch_size x num_labels in ctc_loss_gpu_template()
226 auto log_probs_arg = TensorArg(log_probs, "log_probs", 1); in ctc_loss_gpu_template()
234 int64_t batch_size = log_probs.size(1); in ctc_loss_gpu_template()
235 int64_t num_labels = log_probs.size(2); in ctc_loss_gpu_template()
276 int64_t max_input_length = log_probs.size(0); in ctc_loss_gpu_template()
290 …Tensor log_alpha = at::empty({batch_size, log_probs.size(0), 2*max_target_length+1}, log_probs.opt… in ctc_loss_gpu_template()
291 Tensor neg_log_likelihood = at::empty({batch_size}, log_probs.options()); in ctc_loss_gpu_template()
[all …]
/aosp_15_r20/external/libopus/dnn/torch/lpcnet/models/
H A Dlpcnet.py199 log_probs = torch.log(get_pdf_from_tree(y) + 1e-6)
201 log_probs = torch.log_softmax(y, dim=-1)
203 return log_probs, (gru_a_state, gru_b_state)
226 log_probs, _ = self.sample_rate_network(signals, c, gru_states)
228 return log_probs
H A Dmulti_rate_lpcnet.py314 log_probs = torch.log_softmax(y, dim=-1)
316 return log_probs
/aosp_15_r20/external/tensorflow/tensorflow/lite/kernels/ctc/
H A Dctc_beam_search.h130 std::vector<float>* log_probs, bool merge_repeated) const;
398 int n, std::vector<std::vector<int>>* paths, std::vector<float>* log_probs, in TopPaths() argument
401 TFLITE_DCHECK(log_probs); in TopPaths()
403 log_probs->clear(); in TopPaths()
423 log_probs->push_back(e->newp.total); in TopPaths()
H A Dctc_beam_search_decoder.cc225 std::vector<float> log_probs; in Eval() local
243 &log_probs, merge_repeated)); in Eval()
248 log_probabilities_output[b * top_paths + bp] = log_probs[bp]; in Eval()
/aosp_15_r20/external/tensorflow/tensorflow/core/util/ctc/
H A Dctc_beam_search.h133 std::vector<T>* log_probs, bool merge_repeated) const;
403 int n, std::vector<std::vector<int>>* paths, std::vector<T>* log_probs, in TopPaths() argument
406 CHECK_NOTNULL(log_probs)->clear(); in TopPaths()
427 log_probs->push_back(e->newp.total); in TopPaths()
/aosp_15_r20/external/tensorflow/tensorflow/core/kernels/
H A Dctc_decoder_ops.cc340 std::vector<T> log_probs; in Compute() local
354 &log_probs, merge_repeated_)); in Compute()
359 log_prob_t(b, bp) = log_probs[bp]; in Compute()
/aosp_15_r20/external/pytorch/test/
H A Dtest_nn.py2639 log_probs = torch.randn(50, 3, 15, dtype=torch.float).log_softmax(2)
2642 torch.nn.functional.ctc_loss(log_probs, targets, _input_lengths, target_lengths)
2645 torch.nn.functional.ctc_loss(log_probs, targets, input_lengths, target_lengths)
2652 log_probs = torch.randn(50, 3, 15, dtype=torch.float, device='cuda').log_softmax(2)
2654 torch.nn.functional.ctc_loss(log_probs, targets, input_lengths, target_lengths)
2660 log_probs = torch.randn(50, 3, 15, dtype=torch.float).log_softmax(2)
2662 torch.nn.functional.ctc_loss(log_probs, targets, input_lengths, target_lengths)
2671 …log_probs = torch.randn(input_length, batch_size, vocab_size, dtype=torch.double).log_softmax(2).r…
2676 res_cpu = torch.nn.functional.ctc_loss(log_probs, targets, input_lengths, target_lengths,
2679 grad_cpu, = torch.autograd.grad(res_cpu, log_probs, grad_out)
[all …]
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/functional/
H A Dloss.h737 const Tensor& log_probs, in ctc_loss() argument
745 log_probs, in ctc_loss()
766 /// F::ctc_loss(log_probs, targets, input_lengths, target_lengths,
770 const Tensor& log_probs,
776 log_probs,
/aosp_15_r20/external/pytorch/test/mobile/model_test/
H A Dnn_ops.py341 log_probs = torch.randn(50, 16, 20).log_softmax(2).detach()
351 F.ctc_loss(log_probs, targets, input_lengths, target_lengths),
/aosp_15_r20/external/pytorch/test/cpp/api/
H A Dfunctional.cpp2574 const auto log_probs = in TEST_F() local
2579 F::ctc_loss(log_probs, targets, _input_lengths, target_lengths), in TEST_F()
2584 F::ctc_loss(log_probs, targets, input_lengths, target_lengths_), in TEST_F()
2591 const auto log_probs = in TEST_F() local
2594 F::ctc_loss(log_probs, targets, input_lengths, target_lengths), in TEST_F()
2603 const auto log_probs = in TEST_F() local
2606 log_probs, in TEST_F()
2613 -log_probs.sum(0).slice(1, 0, 1).view_as(loss), loss)); in TEST_F()
2619 const auto log_probs = in TEST_F() local
2622 log_probs, in TEST_F()
[all …]
H A Dmodules.cpp2629 // log_probs actually returns log_proba in TEST_F()
2658 // forward returns the same thing as log_probs in TEST_F()
3197 const auto log_probs = in TEST_F() local
3200 loss->forward(log_probs, targets, input_lengths, target_lengths); in TEST_F()
3203 -log_probs.sum(0).slice(1, 0, 1).view_as(output), output)); in TEST_F()
/aosp_15_r20/external/pytorch/torch/csrc/api/src/nn/modules/
H A Dloss.cpp303 const Tensor& log_probs, in forward() argument
308 log_probs, in forward()
/aosp_15_r20/external/pytorch/tools/autograd/
H A Dderivatives.yaml535 - name: _ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int …
536 …log_probs: _ctc_loss_backward(grad, log_probs, targets, input_lengths, target_lengths, result0, re…
538 - name: _ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_leng…
539 …log_probs: _ctc_loss_backward(grad, log_probs, targets, input_lengths, target_lengths, result0, re…
2649 - name: _cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths…
2650 log_probs: _cudnn_ctc_loss_backward(grad, result0, result1, zero_infinity)
2652 - name: _cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor targe…
2653 log_probs: _cudnn_ctc_loss_backward(grad, result0, result1, zero_infinity)
/aosp_15_r20/external/pytorch/torch/testing/_internal/
H A Dcommon_nn.py3020 def ctcloss_reference(log_probs, targets, input_lengths, target_lengths, blank=0, reduction='mean'): argument
3023 dt = log_probs.dtype
3024 log_probs = log_probs.double() # we need the accuracy as we are not in logspace
3028 for i in range(log_probs.size(1)):
3037 probs = log_probs[:input_length, i].exp()
3038 alpha = log_probs.new_zeros((target_length * 2 + 1,))
/aosp_15_r20/external/pytorch/torch/nn/
H A Dfunctional.py3006 log_probs: Tensor,
3025 …log_probs: :math:`(T, N, C)` or :math:`(T, C)` where `C = number of characters in alphabet includi…
3050 >>> log_probs = torch.randn(50, 16, 20).log_softmax(2).detach().requires_grad_()
3054 >>> loss = F.ctc_loss(log_probs, targets, input_lengths, target_lengths)
3057 if has_torch_function_variadic(log_probs, targets, input_lengths, target_lengths):
3060 (log_probs, targets, input_lengths, target_lengths),
3061 log_probs,
3070 log_probs,
H A Dfunctional.pyi.in326 log_probs: Tensor,
/aosp_15_r20/external/pytorch/torch/nn/modules/
H A Dloss.py1850 - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`,
1975 log_probs: Tensor,
1981 log_probs,
/aosp_15_r20/external/pytorch/test/distributions/
H A Dtest_distributions.py1245 log_probs = dist.log_prob(s)
1246 log_probs_data_flat = log_probs.view(-1)
3940 log_probs = []
3949 log_probs.append(log_prob - log_abs_det_jacobian)
3957 for x in log_probs
3960 self.assertEqual(log_probs[0], log_probs[1])
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/options/
H A Dloss.h518 /// F::ctc_loss(log_probs, targets, input_lengths, target_lengths,
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/modules/
H A Dloss.h586 const Tensor& log_probs,
/aosp_15_r20/external/pytorch/torch/
H A Doverrides.py551 …lambda log_probs, targets, input_lengths, target_lengths, blank=0, reduction="mean", zero_infinity…
859 …lambda log_probs, targets, input_lengths, target_lengths, blank=0, reduction="mean", zero_infinity…

12