conv1d with bias=False

Summary: Under the same setting as the last diff, we support `bias=false`.

Reviewed By: jorgep31415

Differential Revision: D56285842

fbshipit-source-id: 41636d19d2cd7db07ba924606c9cd33999cffdab

Author: copyrightly

backends/vulkan/runtime/graph/ops/impl/Convolution.cpp

@@ -81,15 +81,14 @@ ValueRef prepack_biases(
     ComputeGraph& graph,
     const ValueRef vref,
     const ValueRef weight,
-    const bool transposed) {
+    const bool transposed,
+    const api::StorageType storage_type,
+    const api::GPUMemoryLayout memory_layout) {
   auto sizes = graph.get_sizes_of(weight);
   const int64_t out_channels = transposed ? sizes.at(1) : sizes.at(0);
 
   ValueRef v = graph.add_tensor(
-      {out_channels},
-      graph.get_dtype_of(weight),
-      api::kTexture2D,
-      api::kWidthPacked);
+      {out_channels}, graph.get_dtype_of(weight), storage_type, memory_layout);
   vTensorPtr t = graph.get_tensor(v);
 
   api::ShaderInfo shader = get_nchw_to_image_shader(*t);
@@ -329,7 +328,13 @@ void add_conv2d_node(
 
   ValueRef arg_in = prepack_if_tensor_ref(graph, in);
   ValueRef arg_weight = prepack_weights(graph, weight, method);
-  ValueRef arg_bias = prepack_biases(graph, bias, weight, transposed_val);
+  ValueRef arg_bias = prepack_biases(
+      graph,
+      bias,
+      weight,
+      transposed_val,
+      /* storage_type = */ api::kTexture2D,
+      /* memory_layout = */ api::kWidthPacked);
 
   vTensorPtr t_in = graph.get_tensor(arg_in);
   vTensorPtr t_out = graph.get_tensor(out);
@@ -383,15 +388,16 @@ void add_conv1d_node(
     const ValueRef dilation,
     const ValueRef groups,
     const ValueRef out) {
-  if (graph.val_is_none(bias)) {
-    VK_THROW("conv1d: Null bias is not supported yet!");
-  }
-
   ValueRef arg_in = prepack_if_tensor_ref(graph, in);
   ValueRef arg_weight =
       prepack_if_tensor_ref(graph, weight, graph.memory_layout_of(arg_in));
-  ValueRef arg_bias =
-      prepack_if_tensor_ref(graph, bias, graph.memory_layout_of(arg_in));
+  ValueRef arg_bias = prepack_biases(
+      graph,
+      bias,
+      weight,
+      /*transposed = */ false,
+      /*storage_type = */ api::kTexture3D,
+      /*memory_layout = */ api::kChannelsPacked);
 
   vTensorPtr t_in = graph.get_tensor(arg_in);
   vTensorPtr t_weight = graph.get_tensor(arg_weight);

backends/vulkan/test/op_tests/cases.py

@@ -135,6 +135,17 @@ def get_conv_inputs():
                 [0],
                 6,
             ),
+            (
+                (1, 9, 11),
+                (9, 1, 3),
+                None,
+                [1],
+                [0],
+                [1],
+                False,
+                [0],
+                9,
+            ),
         ]
     )
     return test_suite

backends/vulkan/test/test_vulkan_delegate.py

@@ -672,6 +672,30 @@ def forward(self, x):
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
         )
 
+    def test_vulkan_backend_conv1d_bias_false(self):
+        class Conv1dModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+                self.conv = torch.nn.Conv1d(
+                    in_channels=6,
+                    out_channels=6,
+                    kernel_size=3,
+                    groups=6,
+                    bias=False,
+                )
+
+            def forward(self, x):
+                return self.conv(x)
+
+        conv1d_module = Conv1dModule()
+        sample_inputs = (torch.randn(size=(1, 6, 7), dtype=torch.float32),)
+
+        self.lower_module_and_test_output(
+            conv1d_module,
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
     def test_vulkan_backend_native_layer_norm(self):
         class NativeLayerNormModule(torch.nn.Module):
             def __init__(self):