diff --git a/.gitattributes b/.gitattributes index 908139239ff69dc30df911a79d389ee885770436..1ff238786685f26cecbfe0bced74e97339d7f334 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1431,3 +1431,4 @@ parrot/lib/python3.10/site-packages/opencv_python.libs/libQt5Test-d435aae7.so.5. vllm/lib/python3.10/site-packages/wandb/vendor/pynvml/__pycache__/pynvml.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text vllm/lib/python3.10/site-packages/wandb/vendor/pygments/lexers/__pycache__/_php_builtins.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text vllm/lib/python3.10/site-packages/wandb/sdk/internal/__pycache__/internal_api.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text +openflamingo/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_host.so filter=lfs diff=lfs merge=lfs -text diff --git a/openflamingo/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_host.so b/openflamingo/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_host.so new file mode 100644 index 0000000000000000000000000000000000000000..ed40a4bc764fe9ea14dc2732cbc294053564171c --- /dev/null +++ b/openflamingo/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_host.so @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3a9c6b06d6da647f487427173211c567fe3f4c5cbfe519671699ee43fbefc66d +size 21654328 diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_backward_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..1caa0989425a2a374613794d0044f6edbbb60c29 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_cdist_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _cdist_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cdist_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cdist_backward(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist) -> Tensor") + static at::Tensor call(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist); +}; + +struct TORCH_API _cdist_backward_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_cdist_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_cdist_backward.out(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h new file mode 100644 index 0000000000000000000000000000000000000000..eec07bcdc5f26a3604d6262e4b8cee540b486192 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_cufft_clear_plan_cache.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_cufft_clear_plan_cache(DeviceIndex device_index) -> () +inline void _cufft_clear_plan_cache(at::DeviceIndex device_index) { + return at::_ops::_cufft_clear_plan_cache::call(device_index); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad.h new file mode 100644 index 0000000000000000000000000000000000000000..e07b0a821e104b5eb96ea5e9502916cd0e6898a5 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_dirichlet_grad.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_dirichlet_grad(Tensor x, Tensor alpha, Tensor total) -> Tensor +inline at::Tensor _dirichlet_grad(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total) { + return at::_ops::_dirichlet_grad::call(x, alpha, total); +} + +// aten::_dirichlet_grad.out(Tensor x, Tensor alpha, Tensor total, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _dirichlet_grad_out(at::Tensor & out, const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total) { + return at::_ops::_dirichlet_grad_out::call(x, alpha, total, out); +} +// aten::_dirichlet_grad.out(Tensor x, Tensor alpha, Tensor total, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _dirichlet_grad_outf(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total, at::Tensor & out) { + return at::_ops::_dirichlet_grad_out::call(x, alpha, total, out); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..da9f8c8717ea414f7bddafce2177a6db7bb74d3e --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_embedding_bag_per_sample_weights_backward_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..9e088db3e3e5886f2ade39caa41abd051174502c --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_foreach_sinh_ops.h @@ -0,0 +1,50 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API _foreach_sinh { + using schema = ::std::vector (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sinh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sinh(Tensor[] self) -> Tensor[]") + static ::std::vector call(at::TensorList self); + static ::std::vector redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sinh_ { + using schema = void (at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sinh_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sinh_(Tensor(a!)[] self) -> ()") + static void call(at::TensorList self); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self); +}; + +struct TORCH_API _foreach_sinh_out { + using schema = void (at::TensorList, at::TensorList); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::_foreach_sinh") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") + static void call(at::TensorList self, at::TensorList out); + static void redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_native.h new file mode 100644 index 0000000000000000000000000000000000000000..04ddb0f9c4f223d4733c26b07ec3c88cc6b7e48d --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_fused_adamw_native.h @@ -0,0 +1,26 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adamw(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional & grad_scale={}, const c10::optional & found_inf={}); +TORCH_API void _fused_adamw_out(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional & grad_scale, const c10::optional & found_inf, at::TensorList out); +TORCH_API void _fused_adamw_kernel_cuda_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional & grad_scale={}, const c10::optional & found_inf={}); +TORCH_API ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> _fused_adamw(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional & grad_scale={}, const c10::optional & found_inf={}); +TORCH_API void _fused_adamw_tensor_lr_out(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional & grad_scale, const c10::optional & found_inf, at::TensorList out); +TORCH_API void _fused_adamw_kernel_cuda_(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, const at::Tensor & lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional & grad_scale={}, const c10::optional & found_inf={}); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..bc4a172b23e4e9121b631a6bde1e62101913d55c --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_histogramdd_from_bin_tensors_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _histogramdd_from_bin_tensors(const at::Tensor & self, at::TensorList bins, const c10::optional & weight={}, bool density=false); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dep_token_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dep_token_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..67edd6bd5848407b82f82384717b9c07e3488ff7 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_make_dep_token_cpu_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _make_dep_token(at::TensorOptions options={}, c10::optional memory_format=c10::nullopt); +TORCH_API at::Tensor _make_dep_token(c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_transpose.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_transpose.h new file mode 100644 index 0000000000000000000000000000000000000000..ba819531604e2f2c81aedce6c94832dba6092ad2 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_mps_convolution_transpose.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_mps_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _mps_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template ::value>> + at::Tensor _mps_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::_mps_convolution_transpose(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups) -> Tensor +inline at::Tensor _mps_convolution_transpose_symint(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, padding, output_padding, stride, dilation, groups); +} +namespace symint { + template ::value>> + at::Tensor _mps_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose::call(self, weight, padding, output_padding, stride, dilation, groups); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template ::value>> + at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); +} +namespace symint { + template ::value>> + at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(output_padding), c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(dilation), groups, out); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); +} +namespace symint { + template ::value>> + at::Tensor & _mps_convolution_transpose_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); + } +} + +// aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, SymInt[] padding, SymInt[] output_padding, SymInt[] stride, SymInt[] dilation, SymInt groups, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _mps_convolution_transpose_symint_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); +} +namespace symint { + template ::value>> + at::Tensor & _mps_convolution_transpose_outf(const at::Tensor & self, const at::Tensor & weight, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, c10::SymIntArrayRef stride, c10::SymIntArrayRef dilation, c10::SymInt groups, at::Tensor & out) { + return at::_ops::_mps_convolution_transpose_out::call(self, weight, padding, output_padding, stride, dilation, groups, out); + } +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..36ca51f9fb8160e696c9bf5ffc33b875c4e600a7 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_nested_view_from_buffer_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _nested_view_from_buffer(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, const at::Tensor & offsets); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sum_backward.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sum_backward.h new file mode 100644 index 0000000000000000000000000000000000000000..5deb1b46f518e62746e99c04df32decfbb0fa87c --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_sparse_sum_backward.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor +inline at::Tensor _sparse_sum_backward(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim) { + return at::_ops::_sparse_sum_backward::call(grad, self, dim); +} + +// aten::_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_sum_backward_out(at::Tensor & out, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim) { + return at::_ops::_sparse_sum_backward_out::call(grad, self, dim, out); +} +// aten::_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & _sparse_sum_backward_outf(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { + return at::_ops::_sparse_sum_backward_out::call(grad, self, dim, out); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..670eff51bdf56c0e2fe9fd64a60f3e4d65020c1f --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_to_sparse_csr_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & _to_sparse_csr_out(const at::Tensor & self, c10::optional dense_dim, at::Tensor & out); +TORCH_API at::Tensor dense_to_sparse_csr(const at::Tensor & self, c10::optional dense_dim=c10::nullopt); +TORCH_API at::Tensor coo_to_sparse_csr(const at::Tensor & self, c10::optional dense_dim=c10::nullopt); +TORCH_API at::Tensor sparse_compressed_to_sparse_csr(const at::Tensor & self, c10::optional dense_dim=c10::nullopt); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_meta_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..030f463b2347802cb42dd2feeba397c77cc42666 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bicubic2d_aa_meta_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor _upsample_bicubic2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor _upsample_bicubic2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bicubic2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..55fab16fb10461c6962cc1f107f790d2ffb20002 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_upsample_bilinear2d_aa_cpu_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor _upsample_bilinear2d_aa(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor _upsample_bilinear2d_aa_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & _upsample_bilinear2d_aa_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..ce39c759f24919f49c6250d923664e6c9b586ebe --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/_weight_norm_interface_backward_cpu_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API ::std::tuple _weight_norm_interface_backward(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cuda_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..57c0d6e74969cdbd57373b088e9dd2fcc9b22354 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/adaptive_max_pool3d_backward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor adaptive_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); +TORCH_API at::Tensor & adaptive_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/adjoint.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/adjoint.h new file mode 100644 index 0000000000000000000000000000000000000000..315f8046deccb7c2fff8174e88418a1c209a235f --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/adjoint.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::adjoint(Tensor(a) self) -> Tensor(a) +inline at::Tensor adjoint(const at::Tensor & self) { + return at::_ops::adjoint::call(self); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d.h new file mode 100644 index 0000000000000000000000000000000000000000..f6aca1c62c7b80344ce11d7f4a639d49b07ca897 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/avg_pool3d.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt) { + return at::_ops::avg_pool3d_out::call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); +} +// aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & out) { + return at::_ops::avg_pool3d_out::call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); +} + +// aten::avg_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor +inline at::Tensor avg_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt) { + return at::_ops::avg_pool3d::call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_compositeexplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7f1ed3db998c1a7ca5b31ae5423832fcf154e761 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/batch_norm_backward_reduce_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple batch_norm_backward_reduce_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, bool input_g, bool weight_g, bool bias_g); +TORCH_API ::std::tuple batch_norm_backward_reduce_outf(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, bool input_g, bool weight_g, bool bias_g, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_right_shift.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_right_shift.h new file mode 100644 index 0000000000000000000000000000000000000000..396ddf7dbd77d3729204b0ae63297fc14be32f08 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/bitwise_right_shift.h @@ -0,0 +1,67 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::bitwise_right_shift.Tensor(Tensor self, Tensor other) -> Tensor +inline at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Tensor::call(self, other); +} + +// aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Tensor_out::call(self, other, out); +} +// aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_right_shift_Tensor_out::call(self, other, out); +} + +// aten::bitwise_right_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor +inline at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_right_shift_Tensor_Scalar::call(self, other); +} + +// aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other) { + return at::_ops::bitwise_right_shift_Tensor_Scalar_out::call(self, other, out); +} +// aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { + return at::_ops::bitwise_right_shift_Tensor_Scalar_out::call(self, other, out); +} + +// aten::bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor +inline at::Tensor bitwise_right_shift(const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Scalar_Tensor::call(self, other); +} + +// aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other) { + return at::_ops::bitwise_right_shift_Scalar_Tensor_out::call(self, other, out); +} +// aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & bitwise_right_shift_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { + return at::_ops::bitwise_right_shift_Scalar_Tensor_out::call(self, other, out); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cauchy_compositeexplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cauchy_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..a5562df3361baf619994e16f49b9eef316c8abe9 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cauchy_compositeexplicitautograd_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor cauchy(const at::Tensor & self, double median=0, double sigma=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & cauchy_out(at::Tensor & out, const at::Tensor & self, double median=0, double sigma=1, c10::optional generator=c10::nullopt); +TORCH_API at::Tensor & cauchy_outf(const at::Tensor & self, double median, double sigma, c10::optional generator, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_meta.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_meta.h new file mode 100644 index 0000000000000000000000000000000000000000..e579f6e2dad6b20439767396fcafd5b55646284c --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/ceil_meta.h @@ -0,0 +1,27 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeMetaFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace meta { + +struct TORCH_API structured_ceil : public TensorIteratorBase { + + + void meta(const at::Tensor & self); +}; + +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/conv2d.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/conv2d.h new file mode 100644 index 0000000000000000000000000000000000000000..c5cc39919d544f44c73ed313a5b5e057a4246653 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/conv2d.h @@ -0,0 +1,69 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv2d::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template ::value>> + at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv2d::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), c10::fromIntArrayRefSlow(padding), c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, SymInt[2] stride=1, SymInt[2] padding=0, SymInt[2] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv2d_symint(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv2d::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template ::value>> + at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, c10::SymIntArrayRef stride=c10::SymInt(1), c10::SymIntArrayRef padding=c10::SymInt(0), c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv2d::call(input, weight, bias, stride, padding, dilation, groups); + } +} + +// aten::conv2d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[2] stride=1, str padding="valid", SymInt[2] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv2d_padding::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); +} +namespace symint { + template ::value>> + at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation=1, int64_t groups=1) { + return at::_ops::conv2d_padding::call(input, weight, bias, c10::fromIntArrayRefSlow(stride), padding, c10::fromIntArrayRefSlow(dilation), groups); + } +} + +// aten::conv2d.padding(Tensor input, Tensor weight, Tensor? bias=None, SymInt[2] stride=1, str padding="valid", SymInt[2] dilation=1, SymInt groups=1) -> Tensor +inline at::Tensor conv2d_symint(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv2d_padding::call(input, weight, bias, stride, padding, dilation, groups); +} +namespace symint { + template ::value>> + at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, c10::SymIntArrayRef stride, c10::string_view padding, c10::SymIntArrayRef dilation=c10::SymInt(1), c10::SymInt groups=1) { + return at::_ops::conv2d_padding::call(input, weight, bias, stride, padding, dilation, groups); + } +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cov_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cov_native.h new file mode 100644 index 0000000000000000000000000000000000000000..9ee59ae2ddb310d6b61583a37eb6f664dc333bbd --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cov_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor cov(const at::Tensor & self, int64_t correction=1, const c10::optional & fweights={}, const c10::optional & aweights={}); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cumprod_compositeexplicitautogradnonfunctional_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cumprod_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..d3988955a54119ad93b7b7b00a8ed02bcda7ba39 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/cumprod_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor cumprod(const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & cumprod_(at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfftn_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfftn_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bb600b7a9e499342d9ddc80aee5394f53aba20fd --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/fft_rfftn_native.h @@ -0,0 +1,22 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor fft_rfftn_symint(const at::Tensor & self, at::OptionalSymIntArrayRef s=c10::nullopt, at::OptionalIntArrayRef dim=c10::nullopt, c10::optional norm=c10::nullopt); +TORCH_API at::Tensor & fft_rfftn_symint_out(const at::Tensor & self, at::OptionalSymIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional norm, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/frac_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/frac_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..4252aa4d5b9782e823edad49d0244aa23952698f --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/frac_cpu_dispatch.h @@ -0,0 +1,26 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor frac(const at::Tensor & self); +TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self); +TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor & frac_(at::Tensor & self); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/ger_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/ger_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..49472f20c277743cce7177d4f1862eea63085e42 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/ger_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API ger { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::ger") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "ger(Tensor self, Tensor vec2) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & vec2); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2); +}; + +struct TORCH_API ger_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::ger") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/hamming_window_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/hamming_window_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f17a5572228aab75b6434fbc2fba50ada430049e --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/hamming_window_native.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor hamming_window(int64_t window_length, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_out(int64_t window_length, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_periodic_out(int64_t window_length, bool periodic, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_periodic_alpha_out(int64_t window_length, bool periodic, double alpha, at::Tensor & out); +TORCH_API at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & hamming_window_periodic_alpha_beta_out(int64_t window_length, bool periodic, double alpha, double beta, at::Tensor & out); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/index_fill_compositeexplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/index_fill_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..f94f5aa1224f5cc024b55afb159d164432a53856 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/index_fill_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor index_fill(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & index_fill_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); +TORCH_API at::Tensor & index_fill_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out); +TORCH_API at::Tensor index_fill(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & value); +TORCH_API at::Tensor & index_fill_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & value); +TORCH_API at::Tensor & index_fill_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & value, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/item_compositeimplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/item_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..6648c6622ef814ee942cb359f17150185f8eac08 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/item_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API at::Scalar item(const at::Tensor & self); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/l1_loss.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/l1_loss.h new file mode 100644 index 0000000000000000000000000000000000000000..dacd2090a7b719dcd219edcc50d79d6da64857d7 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/l1_loss.h @@ -0,0 +1,30 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::l1_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor +inline at::Tensor l1_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean) { + return at::_ops::l1_loss::call(self, target, reduction); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..7e060baf63e6b3d760020d5306eb814db4fa5b81 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_ldl_solve_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API linalg_ldl_solve { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_ldl_solve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_ldl_solve(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False) -> Tensor") + static at::Tensor call(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian); +}; + +struct TORCH_API linalg_ldl_solve_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::linalg_ldl_solve") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "linalg_ldl_solve.out(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_slogdet.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_slogdet.h new file mode 100644 index 0000000000000000000000000000000000000000..ffd76e6e0986d39eade11a8874e1978dfbec46d9 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_slogdet.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::linalg_slogdet(Tensor A) -> (Tensor sign, Tensor logabsdet) +inline ::std::tuple linalg_slogdet(const at::Tensor & A) { + return at::_ops::linalg_slogdet::call(A); +} + +// aten::linalg_slogdet.out(Tensor A, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) +inline ::std::tuple linalg_slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, const at::Tensor & A) { + return at::_ops::linalg_slogdet_out::call(A, sign, logabsdet); +} +// aten::linalg_slogdet.out(Tensor A, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) +inline ::std::tuple linalg_slogdet_outf(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet) { + return at::_ops::linalg_slogdet_out::call(A, sign, logabsdet); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vector_norm_meta_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vector_norm_meta_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70d14110cdacb86e3fcd73501454b29b17adeaf9 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/linalg_vector_norm_meta_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace meta { + +TORCH_API at::Tensor linalg_vector_norm(const at::Tensor & self, const at::Scalar & ord=2, at::OptionalIntArrayRef dim=c10::nullopt, bool keepdim=false, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & linalg_vector_norm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & ord=2, at::OptionalIntArrayRef dim=c10::nullopt, bool keepdim=false, c10::optional dtype=c10::nullopt); +TORCH_API at::Tensor & linalg_vector_norm_outf(const at::Tensor & self, const at::Scalar & ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); + +} // namespace meta +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cuda_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..0ad2fd16e07040a6387a04f43e0a8e92001fd7fa --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/log_sigmoid_forward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API ::std::tuple log_sigmoid_forward(const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_out(at::Tensor & output, at::Tensor & buffer, const at::Tensor & self); +TORCH_API ::std::tuple log_sigmoid_forward_outf(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer); + +} // namespace cuda +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..175d42d9973e19b376104b3804796f04468beb27 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/logaddexp2_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API logaddexp2_out { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logaddexp2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API logaddexp2 { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logaddexp2") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logaddexp2(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..cf8ec41865205e75395500fb7255889af71bd82c --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/logit_backward_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API logit_backward_grad_input { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logit_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "grad_input") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logit_backward.grad_input(Tensor grad_output, Tensor self, float? eps=None, *, Tensor(a!) grad_input) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps, at::Tensor & grad_input); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps, at::Tensor & grad_input); +}; + +struct TORCH_API logit_backward { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::logit_backward") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "logit_backward(Tensor grad_output, Tensor self, float? eps=None) -> Tensor") + static at::Tensor call(const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..70e6378179530cd1f66725d6717e3e3425c7ba4e --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/miopen_rnn_compositeexplicitautograd_dispatch.h @@ -0,0 +1,24 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API ::std::tuple miopen_rnn_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state); +TORCH_API ::std::tuple miopen_rnn_outf(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..00ae70a7aae59bc05cccbeffd3f6cbc821b6aac9 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/mkldnn_rnn_layer_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API mkldnn_rnn_layer { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_rnn_layer") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor)") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train); +}; + +struct TORCH_API mkldnn_rnn_layer_out { + using schema = ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::mkldnn_rnn_layer") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") + static ::std::tuple call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); + static ::std::tuple redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cuda_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..fd155b10e62df6fcbe23e4f342951d3121cdfe62 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/multi_margin_loss_backward_cuda_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor multi_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); +TORCH_API at::Tensor & multi_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight, int64_t reduction, at::Tensor & grad_input); + +} // namespace cuda +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/permute_compositeexplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/permute_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..c674af8a2adf0ffec8d5d028834e12824b3b6da0 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/permute_compositeexplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor permute(const at::Tensor & self, at::IntArrayRef dims); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/real_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/real_native.h new file mode 100644 index 0000000000000000000000000000000000000000..75b20319e2da6e700ec529d77e70bb6e57173c41 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/real_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor real(const at::Tensor & self); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/relu_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/relu_native.h new file mode 100644 index 0000000000000000000000000000000000000000..286fcd38471985fc327835c9676278d0f6cef255 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/relu_native.h @@ -0,0 +1,35 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor & relu_out(const at::Tensor & self, at::Tensor & out); +TORCH_API at::Tensor relu(const at::Tensor & self); +TORCH_API at::Tensor & relu_(at::Tensor & self); +TORCH_API at::Tensor NestedTensor_relu(const at::Tensor & self); +TORCH_API at::Tensor & NestedTensor_relu_(at::Tensor & self); +TORCH_API at::Tensor relu_sparse(const at::Tensor & self); +TORCH_API at::Tensor & relu_sparse_(at::Tensor & self); +TORCH_API at::Tensor relu_sparse_csr(const at::Tensor & self); +TORCH_API at::Tensor & relu_sparse_csr_(at::Tensor & self); +TORCH_API at::Tensor mkldnn_relu(const at::Tensor & self); +TORCH_API at::Tensor & mkldnn_relu_(at::Tensor & self); +TORCH_API at::Tensor relu_quantized_cpu(const at::Tensor & self); +TORCH_API at::Tensor & relu_quantized_cpu_(at::Tensor & self); +TORCH_API at::Tensor relu_quantized_cuda(const at::Tensor & self); +TORCH_API at::Tensor & relu_quantized_cuda_(at::Tensor & self); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1a5a36687c79f316f590d5b3089585fd2115fa3a --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/remainder_compositeexplicitautograd_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautograd { + +TORCH_API at::Tensor remainder(const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & remainder_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +TORCH_API at::Tensor & remainder_(at::Tensor & self, const at::Scalar & other); +TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other); +TORCH_API at::Tensor & remainder_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + +} // namespace compositeexplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_native.h new file mode 100644 index 0000000000000000000000000000000000000000..f25da3e640799d8373e249b4815f6b6d43c6cae7 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor resize_as(const at::Tensor & self, const at::Tensor & the_template, c10::optional memory_format=c10::nullopt); +TORCH_API const at::Tensor & resize_as_out(const at::Tensor & self, const at::Tensor & the_template, c10::optional memory_format, const at::Tensor & out); +TORCH_API const at::Tensor & resize_as_(const at::Tensor & self, const at::Tensor & the_template, c10::optional memory_format=c10::nullopt); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h new file mode 100644 index 0000000000000000000000000000000000000000..beb06b63ff4c927d7bad11dbc81e3e7ebff682f3 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/resize_as_sparse_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor resize_as_sparse(const at::Tensor & self, const at::Tensor & the_template); +TORCH_API const at::Tensor & resize_as_sparse_out(const at::Tensor & self, const at::Tensor & the_template, const at::Tensor & out); +TORCH_API const at::Tensor & resize_as_sparse_(const at::Tensor & self, const at::Tensor & the_template); +TORCH_API const at::Tensor & resize_as_sparse_compressed_(const at::Tensor & self, const at::Tensor & the_template); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/select_scatter.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/select_scatter.h new file mode 100644 index 0000000000000000000000000000000000000000..a6a3cb6e9af431341a06b614a0a2aec87fe301fe --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/select_scatter.h @@ -0,0 +1,91 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor +inline at::Tensor select_scatter(const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index) { + return at::_ops::select_scatter::call(self, src, dim, index); +} +namespace symint { + template ::value>> + at::Tensor select_scatter(const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index) { + return at::_ops::select_scatter::call(self, src, dim, index); + } +} + +// aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor +inline at::Tensor select_scatter_symint(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index) { + return at::_ops::select_scatter::call(self, src, dim, index); +} +namespace symint { + template ::value>> + at::Tensor select_scatter(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index) { + return at::_ops::select_scatter::call(self, src, dim, index); + } +} + +// aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); + } +} + +// aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_scatter_outf(const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_scatter_outf(const at::Tensor & self, const at::Tensor & src, int64_t dim, int64_t index, at::Tensor & out) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); + } +} + +// aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_scatter_symint_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_scatter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); + } +} + +// aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & select_scatter_symint_outf(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); +} +namespace symint { + template ::value>> + at::Tensor & select_scatter_outf(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index, at::Tensor & out) { + return at::_ops::select_scatter_out::call(self, src, dim, index, out); + } +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_coo_tensor_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_coo_tensor_native.h new file mode 100644 index 0000000000000000000000000000000000000000..21fbce10c866274c95a573a221622e6eecc30c6d --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/sparse_coo_tensor_native.h @@ -0,0 +1,24 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor sparse_coo_tensor(at::IntArrayRef size, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}); +TORCH_API at::Tensor & sparse_coo_tensor_size_out(at::IntArrayRef size, at::Tensor & out); +TORCH_API at::Tensor sparse_coo_tensor(const at::Tensor & indices, const at::Tensor & values, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}, c10::optional is_coalesced=c10::nullopt); +TORCH_API at::Tensor sparse_coo_tensor(const at::Tensor & indices, const at::Tensor & values, at::IntArrayRef size, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={}, c10::optional is_coalesced=c10::nullopt); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..670661c053004e8c4ea9f332ba6f48f22d5d41f5 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/special_modified_bessel_i0_ops.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_modified_bessel_i0 { + using schema = at::Tensor (const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_modified_bessel_i0") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_modified_bessel_i0(Tensor self) -> Tensor") + static at::Tensor call(const at::Tensor & self); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self); +}; + +struct TORCH_API special_modified_bessel_i0_out { + using schema = at::Tensor & (const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_modified_bessel_i0") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_modified_bessel_i0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/special_softmax_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/special_softmax_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..983d144c4e472bcd8f55eb2b5b9ecd5ce344ee21 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/special_softmax_ops.h @@ -0,0 +1,28 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API special_softmax { + using schema = at::Tensor (const at::Tensor &, int64_t, c10::optional); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::special_softmax") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "special_softmax(Tensor self, int dim, ScalarType? dtype=None) -> Tensor") + static at::Tensor call(const at::Tensor & self, int64_t dim, c10::optional dtype); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional dtype); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/sspaddmm.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/sspaddmm.h new file mode 100644 index 0000000000000000000000000000000000000000..02573affffb8a5782817c0dbc43621e20f21ba46 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/sspaddmm.h @@ -0,0 +1,39 @@ +#pragma once + +// @generated by torchgen/gen.py from Function.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + + +#include + +namespace at { + + +// aten::sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor +inline at::Tensor sspaddmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::sspaddmm::call(self, mat1, mat2, beta, alpha); +} + +// aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sspaddmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1) { + return at::_ops::sspaddmm_out::call(self, mat1, mat2, beta, alpha, out); +} +// aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) +inline at::Tensor & sspaddmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { + return at::_ops::sspaddmm_out::call(self, mat1, mat2, beta, alpha, out); +} + +} diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_backward_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_backward_native.h new file mode 100644 index 0000000000000000000000000000000000000000..bbd0e4502aa39ac5c9f4c5ae6658c01610973f2e --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/tanh_backward_native.h @@ -0,0 +1,23 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace at { +namespace native { +struct TORCH_API structured_tanh_backward_out : public at::meta::structured_tanh_backward { +void impl(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & grad_input); +}; +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_native.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_native.h new file mode 100644 index 0000000000000000000000000000000000000000..7bac6164f04d04ca4afbd1cf15b4efee5c89c310 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/to_sparse_bsr_native.h @@ -0,0 +1,21 @@ +#pragma once + +// @generated by torchgen/gen.py from NativeFunction.h + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + + +namespace at { +namespace native { +TORCH_API at::Tensor to_sparse_bsr(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional dense_dim=c10::nullopt); +} // namespace native +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_compositeimplicitautograd_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_compositeimplicitautograd_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..7e4f17fae2975f8b39749708e7ec0fdb386a5b1d --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unflatten_dense_tensors_compositeimplicitautograd_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeimplicitautograd { + +TORCH_API ::std::vector unflatten_dense_tensors(const at::Tensor & flat, at::TensorList tensors); + +} // namespace compositeimplicitautograd +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..79ef868b9e7808ad0c0a83e9dc210cdf1d39c8ed --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unfold_cuda_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); + +} // namespace cuda +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1cca8aab39827c6524f4742bb07c0c9a378848b0 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/unsqueeze_copy_compositeexplicitautogradnonfunctional_dispatch.h @@ -0,0 +1,23 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace compositeexplicitautogradnonfunctional { + +TORCH_API at::Tensor unsqueeze_copy(const at::Tensor & self, int64_t dim); + +} // namespace compositeexplicitautogradnonfunctional +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_cuda_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..632f69b67466ce199eeffb326eb350e4815454d7 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_nearest2d_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor upsample_nearest2d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_nearest2d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_nearest2d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_cuda_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_cuda_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..aff8419a7157e56037b2c777366e3e021eed67c2 --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/upsample_trilinear3d_cuda_dispatch.h @@ -0,0 +1,28 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cuda { + +TORCH_API at::Tensor upsample_trilinear3d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor upsample_trilinear3d_symint(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); +TORCH_API at::Tensor & upsample_trilinear3d_symint_out(at::Tensor & out, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); +TORCH_API at::Tensor & upsample_trilinear3d_symint_outf(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); + +} // namespace cuda +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/var_cpu_dispatch.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/var_cpu_dispatch.h new file mode 100644 index 0000000000000000000000000000000000000000..1694bffe1c5f9f6aab2e83fc023ac7671f2abe3f --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/var_cpu_dispatch.h @@ -0,0 +1,25 @@ +#pragma once +// @generated by torchgen/gen.py from DispatchKeyFunction.h + +// NB: The implementing C++ file is RegisterDispatchKey.cpp + +// The only #includes we need are for custom classes that have defaults in the C++ API +#include +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { + +namespace cpu { + +TORCH_API at::Tensor var(const at::Tensor & self, at::OptionalIntArrayRef dim=c10::nullopt, const c10::optional & correction=c10::nullopt, bool keepdim=false); +TORCH_API at::Tensor & var_out(at::Tensor & out, const at::Tensor & self, at::OptionalIntArrayRef dim=c10::nullopt, const c10::optional & correction=c10::nullopt, bool keepdim=false); +TORCH_API at::Tensor & var_outf(const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim, at::Tensor & out); + +} // namespace cpu +} // namespace at diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/var_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/var_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..bf8e64dfe690e1394c15ef6037f61ad8b740908b --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/var_ops.h @@ -0,0 +1,116 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API var { + using schema = at::Tensor (const at::Tensor &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var(Tensor self, bool unbiased=True) -> Tensor") + static at::Tensor call(const at::Tensor & self, bool unbiased); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool unbiased); +}; + +struct TORCH_API var_dim { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim); +}; + +struct TORCH_API var_correction { + using schema = at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, const c10::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "correction") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.correction(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim); +}; + +struct TORCH_API var_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API var_correction_out { + using schema = at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, const c10::optional &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "correction_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.correction_out(Tensor self, int[1]? dim=None, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, const c10::optional & correction, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API var_names_dim { + using schema = at::Tensor (const at::Tensor &, at::DimnameList, bool, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names_dim") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim); +}; + +struct TORCH_API var_names_out { + using schema = at::Tensor & (const at::Tensor &, at::DimnameList, bool, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out); +}; + +struct TORCH_API var_correction_names { + using schema = at::Tensor (const at::Tensor &, at::DimnameList, const c10::optional &, bool); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "correction_names") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.correction_names(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False) -> Tensor") + static at::Tensor call(const at::Tensor & self, at::DimnameList dim, const c10::optional & correction, bool keepdim); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, const c10::optional & correction, bool keepdim); +}; + +struct TORCH_API var_correction_names_out { + using schema = at::Tensor & (const at::Tensor &, at::DimnameList, const c10::optional &, bool, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::var") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "correction_names_out") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "var.correction_names_out(Tensor self, Dimname[1] dim, *, Scalar? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, at::DimnameList dim, const c10::optional & correction, bool keepdim, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, const c10::optional & correction, bool keepdim, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/xlogy_ops.h b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/xlogy_ops.h new file mode 100644 index 0000000000000000000000000000000000000000..ca01874bf8e98da0aa9555bef423f950cf15746c --- /dev/null +++ b/videollama2/lib/python3.10/site-packages/torch/include/ATen/ops/xlogy_ops.h @@ -0,0 +1,105 @@ +#pragma once + +// @generated by torchgen/gen.py from Operator.h + +#include +#include + +// Forward declarations of any types needed in the operator signatures. +// We can't directly include these classes because it will cause circular include dependencies. +// This file is included by TensorBody.h, which defines the Tensor class. +#include + +namespace at { +namespace _ops { + + +struct TORCH_API xlogy_Tensor { + using schema = at::Tensor (const at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy.Tensor(Tensor self, Tensor other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API xlogy_Scalar_Self { + using schema = at::Tensor (const at::Scalar &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_Self") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy.Scalar_Self(Scalar self, Tensor other) -> Tensor") + static at::Tensor call(const at::Scalar & self, const at::Tensor & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other); +}; + +struct TORCH_API xlogy_Scalar_Other { + using schema = at::Tensor (const at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_Other") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy.Scalar_Other(Tensor self, Scalar other) -> Tensor") + static at::Tensor call(const at::Tensor & self, const at::Scalar & other); + static at::Tensor redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API xlogy__Tensor { + using schema = at::Tensor & (at::Tensor &, const at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Tensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Tensor & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other); +}; + +struct TORCH_API xlogy__Scalar_Other { + using schema = at::Tensor & (at::Tensor &, const at::Scalar &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy_") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "Scalar_Other") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy_.Scalar_Other(Tensor(a!) self, Scalar other) -> Tensor(a!)") + static at::Tensor & call(at::Tensor & self, const at::Scalar & other); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other); +}; + +struct TORCH_API xlogy_OutTensor { + using schema = at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "OutTensor") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy.OutTensor(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API xlogy_OutScalar_Self { + using schema = at::Tensor & (const at::Scalar &, const at::Tensor &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "OutScalar_Self") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy.OutScalar_Self(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out); +}; + +struct TORCH_API xlogy_OutScalar_Other { + using schema = at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &); + using ptr_schema = schema*; + // See Note [static constexpr char* members for windows NVCC] + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(name, "aten::xlogy") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(overload_name, "OutScalar_Other") + STATIC_CONSTEXPR_STR_INL_EXCEPT_WIN_CUDA(schema_str, "xlogy.OutScalar_Other(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") + static at::Tensor & call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); + static at::Tensor & redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out); +}; + +}} // namespace at::_ops diff --git a/vllm/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/__pycache__/audio_classification.cpython-310.pyc b/vllm/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/__pycache__/audio_classification.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..07e27fcbcd0244e3534f85a764e1ba208e059749 Binary files /dev/null and b/vllm/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/__pycache__/audio_classification.cpython-310.pyc differ diff --git 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