aten.full_like.default (#3843)

Summary:

Implement aten.full_like.default, which is required in OCR full model. Reuse the implementation of aten.full.default

```
func: full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
func: full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor
```

The major difference between full and full_like is the first argument, which full is an integer list and full_like is an input tensor. We can reuse lots of code here. And to support dynamic reshape, just add a condition in resize_full_node to determine the out_sizes.

Reviewed By: yipjustin

Differential Revision: D58121891

backends/vulkan/partitioner/supported_ops.py

@@ -117,6 +117,7 @@ def __contains__(self, op):
     exir_ops.edge.aten.arange.start_step,
     exir_ops.edge.aten.clone.default,
     exir_ops.edge.aten.full.default,
+    exir_ops.edge.aten.full_like.default,
 ]
 
 

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

@@ -20,14 +20,19 @@ void resize_full_node(
     const std::vector<ArgGroup>& args,
     const std::vector<ValueRef>& extra_args) {
   vTensorPtr out = graph->get_tensor(args[0].refs[0]);
-  std::vector<int64_t> out_sizes = *graph->get_int_list(extra_args[0]);
+  std::vector<int64_t> out_sizes;
+  if (graph->val_is_tensor(extra_args[0])) {
+    out_sizes = graph->get_tensor(extra_args[0])->sizes();
+  } else {
+    out_sizes = *graph->get_int_list(extra_args[0]);
+  }
 
   out->virtual_resize(out_sizes);
 }
 
 void add_full_node(
     ComputeGraph& graph,
-    const ValueRef size,
+    const ValueRef size_or_in, //IntListPtr when op is full and vTensorPtr if is full_like
     const ValueRef fill_value,
     const ValueRef out) {
   float fill_value_val = graph.extract_scalar<float>(fill_value);
@@ -54,15 +59,20 @@ void add_full_node(
       {SV(t_out->packed_dim_whcn_idx())},
       // Resizing Logic
       resize_full_node,
-      {size}));
+      {size_or_in}));
 }
 
 void full(ComputeGraph& graph, const std::vector<ValueRef>& args) {
   return add_full_node(graph, args[0], args[1], args[6]);
 }
 
+void full_like(ComputeGraph& graph, const std::vector<ValueRef>& args) {
+  return add_full_node(graph, args[0], args[1], args[7]);
+}
+
 REGISTER_OPERATORS {
   VK_REGISTER_OP(aten.full.default, full);
+  VK_REGISTER_OP(aten.full_like.default, full_like);
 }
 
 } // namespace vkcompute

backends/vulkan/test/op_tests/cases.py

@@ -303,6 +303,17 @@ def get_full_inputs():
     return test_suite
 
 
+def get_full_like_inputs():
+    test_suite = VkTestSuite(
+        [
+            ((S1, S2), 4.0),
+            ((M, M1, M2), -3.5),
+            ((L, M, M1, M2), 9.876),
+        ]
+    )
+    return test_suite
+
+
 def get_select_int_inputs():
     test_suite = VkTestSuite(
         [
@@ -909,6 +920,7 @@ def get_arange_inputs():
     "aten.convolution.default": get_conv_inputs(),
     "aten.native_layer_norm.default": get_native_layer_norm_inputs(),
     "aten.full.default": get_full_inputs(),
+    "aten.full_like.default": get_full_like_inputs(),
     "aten.select.int": get_select_int_inputs(),
     "aten.select_copy.int": get_select_int_inputs(),
     "aten.permute.default": get_permute_inputs(),

backends/vulkan/test/test_vulkan_delegate.py

@@ -971,6 +971,22 @@ def forward(self, x):
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
         )
 
+    def test_vulkan_backend_full_like(self):
+        class FullLikeModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return torch.full_like(x, 42.0)
+
+        sample_inputs = (torch.randn(size=(2, 3, 4, 5), dtype=torch.float32),)
+
+        self.lower_module_and_test_output(
+            FullLikeModule(),
+            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):