register view, reshape and select

Summary:
- We register `select`, `unsqueeze` and `view` in `vulkan_partitioner.py` in order to run vulkan_delegate test (Python e2e test). The latter two might be used to implement `bmm` and `addmm`, so I want to make sure they work.
- We register `reshape` in `View.cpp` explicitly. `reshape` is implemented through `_reshape_alias` (see [this](https://www.internalfb.com/code/fbsource/[a3dd6401f00d73f09bbdea63887fef54ea2c6dd2]/fbcode/caffe2/aten/src/ATen/native/native_functions.yaml?lines=4872-4881)) which is [decomposed as `view`](https://www.internalfb.com/code/fbsource/[bbb783ae1cff98b3b549da3edd845dde946d3da8]/xplat/caffe2/torch/_decomp/decompositions.py?lines=3669-3672). For codegen test, we still need to register the op, otherwise there is error
```
C++ exception with description "Exception raised from get_op_fn at xplat/executorch/backends/vulkan/runtime/graph/ops/OperatorRegistry.cpp:20: (it != table_.end()) is false! Could not find operator with name aten.reshape.default" thrown in the test body.
```

Reviewed By: yipjustin, liuk22

Differential Revision: D56454941

fbshipit-source-id: c83e6fb97d9cf9019cc6e786508f353a22236931

Author: copyrightly

backends/vulkan/partitioner/vulkan_partitioner.py

@@ -52,6 +52,10 @@ def is_node_supported(self, submodules, node: torch.fx.Node) -> bool:
             exir_ops.edge.aten.convolution.default,
             # Normalization
             exir_ops.edge.aten.native_layer_norm.default,
+            # Shape-related operators
+            exir_ops.edge.aten.select_copy.int,
+            exir_ops.edge.aten.unsqueeze_copy.default,
+            exir_ops.edge.aten.view_copy.default,
             # Other
             operator.getitem,
             exir_ops.edge.aten.full.default,

backends/vulkan/test/test_vulkan_delegate.py

@@ -732,3 +732,69 @@ def forward(self, x):
             sample_inputs,
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
         )
+
+    def test_vulkan_backend_reshape(self):
+        class ReshapeModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return torch.reshape(x, [-1, x.size(-1)])
+
+        sample_inputs = (torch.randn(size=(5, 3, 4), dtype=torch.float32),)
+
+        self.lower_module_and_test_output(
+            ReshapeModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
+    def test_vulkan_backend_view(self):
+        class ViewModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return x.view([-1, x.size(-1)])
+
+        sample_inputs = (torch.randn(size=(3, 2, 3, 4), dtype=torch.float32),)
+
+        self.lower_module_and_test_output(
+            ViewModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
+    def test_vulkan_backend_unsqueeze(self):
+        class UnsqueezeModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                x = torch.unsqueeze(x, 1)
+                x = torch.unsqueeze(x, 0)
+                return x
+
+        sample_inputs = (torch.randn(size=(3,), dtype=torch.float32),)
+
+        self.lower_module_and_test_output(
+            UnsqueezeModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
+    def test_vulkan_backend_select(self):
+        class SelectModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return x[0][3]
+
+        sample_inputs = (torch.randn(size=(3, 6, 2, 7), dtype=torch.float32),)
+
+        self.lower_module_and_test_output(
+            SelectModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )