Merge pull request #940 from LaurentMazare/pytorch-2.7.0

Update for PyTorch 2.7.0.

Author: LaurentMazare

CHANGELOG.md

@@ -7,6 +7,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## Unreleased
 ### Changed
 
+## v0.20.0
+### Changed
+- PyTorch v2.7 support
+
 ## v0.19.0
 ### Changed
 - PyTorch v2.6 support

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "tch"
-version = "0.19.0"
+version = "0.20.0"
 authors = ["Laurent Mazare <[email protected]>"]
 edition = "2021"
 build = "build.rs"
@@ -22,7 +22,7 @@ libc = "0.2.0"
 ndarray = "0.16.1"
 rand = "0.8"
 thiserror = "1"
-torch-sys = { version = "0.19.0", path = "torch-sys" }
+torch-sys = { version = "0.20.0", path = "torch-sys" }
 zip = "0.6"
 half = "2"
 safetensors = "0.3.0"

README.md

@@ -18,7 +18,7 @@ The code generation part for the C api on top of libtorch comes from
 
 ## Getting Started
 
-This crate requires the C++ PyTorch library (libtorch) in version *v2.6.0* to be available on
+This crate requires the C++ PyTorch library (libtorch) in version *v2.7.0* to be available on
 your system. You can either:
 
 - Use the system-wide libtorch installation (default).
@@ -85,7 +85,7 @@ seem to include `libtorch.a` by default so this would have to be compiled
 manually, e.g. via the following:
 
 ```bash
-git clone -b v2.6.0 --recurse-submodule https://github.com/pytorch/pytorch.git pytorch-static --depth 1
+git clone -b v2.7.0 --recurse-submodule https://github.com/pytorch/pytorch.git pytorch-static --depth 1
 cd pytorch-static
 USE_CUDA=OFF BUILD_SHARED_LIBS=OFF python setup.py build
 # export LIBTORCH to point at the build directory in pytorch-static.

examples/python-extension/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "tch-ext"
-version = "0.2.0"
+version = "0.20.0"
 authors = ["Laurent Mazare <[email protected]>"]
 edition = "2021"
 build = "build.rs"
@@ -18,6 +18,6 @@ crate-type = ["cdylib"]
 
 [dependencies]
 pyo3 = { version = "0.24", features = ["extension-module"] }
-pyo3-tch = { path = "../../pyo3-tch", version = "0.19.0" }
-tch = { path = "../..", features = ["python-extension"], version = "0.19.0" }
-torch-sys = { path = "../../torch-sys", features = ["python-extension"], version = "0.19.0" }
+pyo3-tch = { path = "../../pyo3-tch", version = "0.20.0" }
+tch = { path = "../..", features = ["python-extension"], version = "0.20.0" }
+torch-sys = { path = "../../torch-sys", features = ["python-extension"], version = "0.20.0" }

gen/gen.ml

@@ -883,7 +883,7 @@ let run
 
 let () =
   run
-    ~yaml_filename:"third_party/pytorch/Declarations-v2.6.0.yaml"
+    ~yaml_filename:"third_party/pytorch/Declarations-v2.7.0.yaml"
     ~cpp_filename:"torch-sys/libtch/torch_api_generated"
     ~ffi_filename:"torch-sys/src/c_generated.rs"
     ~wrapper_filename:"src/wrappers/tensor_generated.rs"

pyo3-tch/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "pyo3-tch"
-version = "0.19.0"
+version = "0.20.0"
 authors = ["Laurent Mazare <[email protected]>"]
 edition = "2021"
 build = "build.rs"
@@ -12,6 +12,6 @@ categories = ["science"]
 license = "MIT/Apache-2.0"
 
 [dependencies]
-tch = { path = "..", features = ["python-extension"], version = "0.19.0" }
-torch-sys = { path = "../torch-sys", features = ["python-extension"], version = "0.19.0" }
-pyo3 = { version = "0.24", features = ["extension-module"] }
+tch = { path = "..", features = ["python-extension"], version = "0.20.0" }
+torch-sys = { path = "../torch-sys", features = ["python-extension"], version = "0.20.0" }
+pyo3 = { version = "0.24", features = ["extension-module"] }

src/wrappers/tensor_fallible_generated.rs

@@ -2060,6 +2060,46 @@ impl Tensor {
         Ok(Tensor { c_tensor: c_tensors[0] })
     }
 
+    pub fn f_internal_dyn_quant_matmul_4bit(
+        inp: &Tensor,
+        packed_weights: &Tensor,
+        block_size: i64,
+        in_features: i64,
+        out_features: i64,
+    ) -> Result<Tensor, TchError> {
+        let mut c_tensors = [std::ptr::null_mut(); 1];
+        unsafe_torch_err!(atg__dyn_quant_matmul_4bit(
+            c_tensors.as_mut_ptr(),
+            inp.c_tensor,
+            packed_weights.c_tensor,
+            block_size,
+            in_features,
+            out_features
+        ));
+        Ok(Tensor { c_tensor: c_tensors[0] })
+    }
+
+    pub fn f_internal_dyn_quant_pack_4bit_weight<T: Borrow<Tensor>>(
+        weights: &Tensor,
+        scales_zeros: &Tensor,
+        bias: Option<T>,
+        block_size: i64,
+        in_features: i64,
+        out_features: i64,
+    ) -> Result<Tensor, TchError> {
+        let mut c_tensors = [std::ptr::null_mut(); 1];
+        unsafe_torch_err!(atg__dyn_quant_pack_4bit_weight(
+            c_tensors.as_mut_ptr(),
+            weights.c_tensor,
+            scales_zeros.c_tensor,
+            bias.as_ref().map_or(std::ptr::null_mut(), |t| t.borrow().c_tensor),
+            block_size,
+            in_features,
+            out_features
+        ));
+        Ok(Tensor { c_tensor: c_tensors[0] })
+    }
+
     pub fn f_internal_efficient_attention_backward<T: Borrow<Tensor>>(
         grad_out_: &Tensor,
         query: &Tensor,
@@ -2900,8 +2940,8 @@ impl Tensor {
         max_k: i64,
         dropout_p: f64,
         is_causal: bool,
-        philox_seed: &Tensor,
-        philox_offset: &Tensor,
+        rng_state: &Tensor,
+        unused: &Tensor,
         scale: impl Into<Option<f64>>,
         window_size_left: impl Into<Option<i64>>,
         window_size_right: impl Into<Option<i64>>,
@@ -2924,8 +2964,8 @@ impl Tensor {
             max_k,
             dropout_p,
             if is_causal { 1 } else { 0 },
-            philox_seed.c_tensor,
-            philox_offset.c_tensor,
+            rng_state.c_tensor,
+            unused.c_tensor,
             scale.unwrap_or(std::f64::NAN),
             scale.is_none() as i8,
             window_size_left.unwrap_or(0i64),
@@ -5783,6 +5823,33 @@ impl Tensor {
         ))
     }
 
+    pub fn f_internal_scaled_grouped_mm<T: Borrow<Tensor>>(
+        &self,
+        mat2: &Tensor,
+        scale_a: &Tensor,
+        scale_b: &Tensor,
+        offs: Option<T>,
+        bias: Option<T>,
+        scale_result: Option<T>,
+        out_dtype: impl Into<Option<Kind>>,
+        use_fast_accum: bool,
+    ) -> Result<Tensor, TchError> {
+        let mut c_tensors = [std::ptr::null_mut(); 1];
+        unsafe_torch_err!(atg__scaled_grouped_mm(
+            c_tensors.as_mut_ptr(),
+            self.c_tensor,
+            mat2.c_tensor,
+            scale_a.c_tensor,
+            scale_b.c_tensor,
+            offs.as_ref().map_or(std::ptr::null_mut(), |t| t.borrow().c_tensor),
+            bias.as_ref().map_or(std::ptr::null_mut(), |t| t.borrow().c_tensor),
+            scale_result.as_ref().map_or(std::ptr::null_mut(), |t| t.borrow().c_tensor),
+            out_dtype.into().map_or(-1, |s| s.c_int()),
+            if use_fast_accum { 1 } else { 0 }
+        ));
+        Ok(Tensor { c_tensor: c_tensors[0] })
+    }
+
     pub fn f_internal_scaled_mm<T: Borrow<Tensor>>(
         &self,
         mat2: &Tensor,
@@ -35234,6 +35301,7 @@ impl Tensor {
         normalized: bool,
         onesided: bool,
         return_complex: bool,
+        align_to_window: bool,
     ) -> Result<Tensor, TchError> {
         let hop_length = hop_length.into();
         let win_length = win_length.into();
@@ -35249,7 +35317,8 @@ impl Tensor {
             window.as_ref().map_or(std::ptr::null_mut(), |t| t.borrow().c_tensor),
             if normalized { 1 } else { 0 },
             if onesided { 1 } else { 0 },
-            if return_complex { 1 } else { 0 }
+            if return_complex { 1 } else { 0 },
+            if align_to_window { 1 } else { 0 }
         ));
         Ok(Tensor { c_tensor: c_tensors[0] })
     }
@@ -35265,6 +35334,7 @@ impl Tensor {
         normalized: bool,
         onesided: bool,
         return_complex: bool,
+        align_to_window: bool,
     ) -> Result<Tensor, TchError> {
         let hop_length = hop_length.into();
         let win_length = win_length.into();
@@ -35283,7 +35353,8 @@ impl Tensor {
             pad_mode.len() as i32,
             if normalized { 1 } else { 0 },
             if onesided { 1 } else { 0 },
-            if return_complex { 1 } else { 0 }
+            if return_complex { 1 } else { 0 },
+            if align_to_window { 1 } else { 0 }
         ));
         Ok(Tensor { c_tensor: c_tensors[0] })
     }

src/wrappers/tensor_generated.rs

@@ -1231,6 +1231,42 @@ impl Tensor {
         Tensor::f_internal_dirichlet_grad_out(out, x, alpha, total).unwrap()
     }
 
+    pub fn internal_dyn_quant_matmul_4bit(
+        inp: &Tensor,
+        packed_weights: &Tensor,
+        block_size: i64,
+        in_features: i64,
+        out_features: i64,
+    ) -> Tensor {
+        Tensor::f_internal_dyn_quant_matmul_4bit(
+            inp,
+            packed_weights,
+            block_size,
+            in_features,
+            out_features,
+        )
+        .unwrap()
+    }
+
+    pub fn internal_dyn_quant_pack_4bit_weight<T: Borrow<Tensor>>(
+        weights: &Tensor,
+        scales_zeros: &Tensor,
+        bias: Option<T>,
+        block_size: i64,
+        in_features: i64,
+        out_features: i64,
+    ) -> Tensor {
+        Tensor::f_internal_dyn_quant_pack_4bit_weight(
+            weights,
+            scales_zeros,
+            bias,
+            block_size,
+            in_features,
+            out_features,
+        )
+        .unwrap()
+    }
+
     pub fn internal_efficient_attention_backward<T: Borrow<Tensor>>(
         grad_out_: &Tensor,
         query: &Tensor,
@@ -1856,8 +1892,8 @@ impl Tensor {
         max_k: i64,
         dropout_p: f64,
         is_causal: bool,
-        philox_seed: &Tensor,
-        philox_offset: &Tensor,
+        rng_state: &Tensor,
+        unused: &Tensor,
         scale: impl Into<Option<f64>>,
         window_size_left: impl Into<Option<i64>>,
         window_size_right: impl Into<Option<i64>>,
@@ -1875,8 +1911,8 @@ impl Tensor {
             max_k,
             dropout_p,
             is_causal,
-            philox_seed,
-            philox_offset,
+            rng_state,
+            unused,
             scale,
             window_size_left,
             window_size_right,
@@ -3488,6 +3524,30 @@ impl Tensor {
         .unwrap()
     }
 
+    pub fn internal_scaled_grouped_mm<T: Borrow<Tensor>>(
+        &self,
+        mat2: &Tensor,
+        scale_a: &Tensor,
+        scale_b: &Tensor,
+        offs: Option<T>,
+        bias: Option<T>,
+        scale_result: Option<T>,
+        out_dtype: impl Into<Option<Kind>>,
+        use_fast_accum: bool,
+    ) -> Tensor {
+        self.f_internal_scaled_grouped_mm(
+            mat2,
+            scale_a,
+            scale_b,
+            offs,
+            bias,
+            scale_result,
+            out_dtype,
+            use_fast_accum,
+        )
+        .unwrap()
+    }
+
     pub fn internal_scaled_mm<T: Borrow<Tensor>>(
         &self,
         mat2: &Tensor,
@@ -17844,9 +17904,19 @@ impl Tensor {
         normalized: bool,
         onesided: bool,
         return_complex: bool,
+        align_to_window: bool,
     ) -> Tensor {
-        self.f_stft(n_fft, hop_length, win_length, window, normalized, onesided, return_complex)
-            .unwrap()
+        self.f_stft(
+            n_fft,
+            hop_length,
+            win_length,
+            window,
+            normalized,
+            onesided,
+            return_complex,
+            align_to_window,
+        )
+        .unwrap()
     }
 
     pub fn stft_center<T: Borrow<Tensor>>(
@@ -17860,6 +17930,7 @@ impl Tensor {
         normalized: bool,
         onesided: bool,
         return_complex: bool,
+        align_to_window: bool,
     ) -> Tensor {
         self.f_stft_center(
             n_fft,
@@ -17871,6 +17942,7 @@ impl Tensor {
             normalized,
             onesided,
             return_complex,
+            align_to_window,
         )
         .unwrap()
     }

torch-sys/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "torch-sys"
-version = "0.19.0"
+version = "0.20.0"
 authors = ["Laurent Mazare <[email protected]>"]
 edition = "2021"
 build = "build.rs"