Merge pull request #1461 from huggingface/metal-conv

Adding the convolutions (1d + 2d) to candle on metal.

candle-core/src/metal_backend.rs

@@ -782,12 +782,72 @@ impl BackendStorage for MetalStorage {
 
     fn conv1d(
         &self,
-        _l: &Layout,
-        _kernel: &Self,
-        _kernel_l: &Layout,
-        _params: &ParamsConv1D,
+        layout: &Layout,
+        kernel: &Self,
+        kernel_l: &Layout,
+        params: &ParamsConv1D,
     ) -> Result<Self> {
-        crate::bail!("conv1d metal")
+        let device = self.device().clone();
+        let shape = layout.shape();
+        let dims = shape.dims();
+        let strides = layout.stride();
+
+        let stride = params.stride;
+        let dilation = params.dilation;
+        let padding = params.padding;
+        let k_size = params.k_size;
+        let l_out = (dims[2] + 2 * padding - dilation * (k_size - 1) - 1) / stride + 1;
+        let dst_el = dims[0] * l_out * dims[1] * k_size;
+        let dst = self
+            .device
+            .new_buffer(dst_el, self.dtype, "conv1d_im2col")?;
+        let command_buffer = self.device.command_buffer()?;
+        let name = match self.dtype {
+            DType::F32 => "im2col1d_f32",
+            dtype => crate::bail!("conv1d metal {dtype:?} not implemented"),
+        };
+        candle_metal_kernels::call_im2col1d_strided(
+            &self.device.device,
+            &command_buffer,
+            &self.device.kernels,
+            name,
+            layout.shape().dims(),
+            strides,
+            (k_size, stride, padding, dilation),
+            &self.buffer,
+            layout.start_offset() * self.dtype.size_in_bytes(),
+            &dst,
+        )
+        .map_err(MetalError::from)?;
+        let col = Self {
+            buffer: dst,
+            device,
+            dtype: self.dtype,
+        };
+        let l_out = params.l_out();
+        let b = params.b_size;
+        let n = params.c_out;
+        let k = params.k_size * params.c_in;
+        let m = l_out;
+        let col_l = Layout::contiguous((b, m, k));
+        let res = if kernel_l.is_contiguous() {
+            let kernel_l = Layout::contiguous_with_offset((1, n, k), kernel_l.start_offset())
+                .transpose(1, 2)?
+                .broadcast_as((b, k, n))?;
+            col.matmul(kernel, (b, m, n, k), &col_l, &kernel_l)?
+        } else {
+            // Make the kernel contiguous if not already the case.
+            let mut kernel_c = self.device().zeros_impl(kernel_l.shape(), kernel.dtype())?;
+            kernel.copy_strided_src(&mut kernel_c, 0, kernel_l)?;
+            let kernel_l = Layout::contiguous_with_offset((1, n, k), kernel_l.start_offset())
+                .transpose(1, 2)?
+                .broadcast_as((b, k, n))?;
+            col.matmul(kernel, (b, m, n, k), &col_l, &kernel_l)?
+        };
+        let res_l = Layout::contiguous((b, l_out, n)).transpose(1, 2)?;
+        let mut res_t = self.device().zeros_impl(res_l.shape(), res.dtype())?;
+        res.copy_strided_src(&mut res_t, 0, &res_l)?;
+        Ok(res_t)
     }
 
     fn conv_transpose1d(
@@ -802,12 +862,79 @@ impl BackendStorage for MetalStorage {
 
     fn conv2d(
         &self,
-        _l: &Layout,
-        _kernel: &Self,
-        _kernel_l: &Layout,
-        _params: &ParamsConv2D,
+        layout: &Layout,
+        kernel: &Self,
+        kernel_l: &Layout,
+        params: &ParamsConv2D,
     ) -> Result<Self> {
-        crate::bail!("conv2d metal")
+        let device = self.device().clone();
+        let shape = layout.shape();
+        let dims = shape.dims();
+
+        let stride = params.stride;
+        let dilation = params.dilation;
+        let padding = params.padding;
+        let h_k = params.k_h;
+        let w_k = params.k_w;
+        let h = dims[2];
+        let w = dims[3];
+        let h_out = (h + 2 * padding - dilation * (h_k - 1) - 1) / stride + 1;
+        let w_out = (w + 2 * padding - dilation * (w_k - 1) - 1) / stride + 1;
+        let dst_el = dims[0] * h_out * w_out * dims[1] * h_k * w_k;
+
+        let dst = self
+            .device
+            .new_buffer(dst_el, self.dtype, "conv2d_im2col")?;
+        let command_buffer = self.device.command_buffer()?;
+        let name = match self.dtype {
+            DType::F32 => "im2col_f32",
+            dtype => crate::bail!("conv1d metal {dtype:?} not implemented"),
+        };
+        candle_metal_kernels::call_im2col_strided(
+            &self.device.device,
+            &command_buffer,
+            &self.device.kernels,
+            name,
+            layout.shape().dims(),
+            layout.stride(),
+            (h_k, w_k, stride, padding, dilation),
+            &self.buffer,
+            layout.start_offset() * self.dtype.size_in_bytes(),
+            &dst,
+        )
+        .map_err(MetalError::from)?;
+        let col = Self {
+            buffer: dst,
+            device,
+            dtype: self.dtype,
+        };
+        let h_out = params.out_h();
+        let w_out = params.out_w();
+        let b = params.b_size;
+        let n = params.c_out;
+        let k = params.k_h * params.k_w * params.c_in;
+        let m = h_out * w_out;
+        let col_l = Layout::contiguous((b, m, k));
+        let res = if kernel_l.is_contiguous() {
+            let kernel_l = Layout::contiguous_with_offset((1, n, k), kernel_l.start_offset())
+                .transpose(1, 2)?
+                .broadcast_as((b, k, n))?;
+            col.matmul(kernel, (b, m, n, k), &col_l, &kernel_l)?
+        } else {
+            // Make the kernel contiguous if not already the case.
+            let mut kernel_c = self.device().zeros_impl(kernel_l.shape(), kernel.dtype())?;
+            kernel.copy_strided_src(&mut kernel_c, 0, kernel_l)?;
+            let kernel_l = Layout::contiguous_with_offset((1, n, k), kernel_l.start_offset())
+                .transpose(1, 2)?
+                .broadcast_as((b, k, n))?;
+            col.matmul(kernel, (b, m, n, k), &col_l, &kernel_l)?
+        };
+        let res_l = Layout::contiguous((b, h_out, w_out, n))
+            .transpose(1, 2)?
+            .transpose(1, 3)?;
+        let mut res_t = self.device().zeros_impl(res_l.shape(), res.dtype())?;
+        res.copy_strided_src(&mut res_t, 0, &res_l)?;
+        Ok(res_t)
     }
 
     fn conv_transpose2d(