Creation ops (#3877)

Summary:
Pull Request resolved: #3877

Add more creation ops (ones/ones_like/zeros/zeros_like). Some are needed in OCR full model. Reuse full's implementation. Register them in Full.cpp

Reviewed By: copyrightly, SS-JIA

Differential Revision: D58247380

fbshipit-source-id: a31249396850a3c8426cda74bd6b6c9595bd2484

Author: Yujie Hui

backends/vulkan/partitioner/supported_ops.py

@@ -118,6 +118,10 @@ def __contains__(self, op):
     exir_ops.edge.aten.clone.default,
     exir_ops.edge.aten.full.default,
     exir_ops.edge.aten.full_like.default,
+    exir_ops.edge.aten.ones.default,
+    exir_ops.edge.aten.ones_like.default,
+    exir_ops.edge.aten.zeros.default,
+    exir_ops.edge.aten.zeros_like.default,
 ]
 
 

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

@@ -64,16 +64,26 @@ void add_full_node(
 }
 
 void full(ComputeGraph& graph, const std::vector<ValueRef>& args) {
-  return add_full_node(graph, args[0], args[1], args[6]);
+  return add_full_node(graph, args[0], args[1], args[args.size() - 1]);
 }
 
-void full_like(ComputeGraph& graph, const std::vector<ValueRef>& args) {
-  return add_full_node(graph, args[0], args[1], args[7]);
+void zeros(ComputeGraph& graph, const std::vector<ValueRef>& args) {
+  return add_full_node(
+      graph, args[0], graph.add_scalar<int64_t>(0), args[args.size() - 1]);
+}
+
+void ones(ComputeGraph& graph, const std::vector<ValueRef>& args) {
+  return add_full_node(
+      graph, args[0], graph.add_scalar<int64_t>(1), args[args.size() - 1]);
 }
 
 REGISTER_OPERATORS {
   VK_REGISTER_OP(aten.full.default, full);
-  VK_REGISTER_OP(aten.full_like.default, full_like);
+  VK_REGISTER_OP(aten.full_like.default, full);
+  VK_REGISTER_OP(aten.zeros.default, zeros);
+  VK_REGISTER_OP(aten.zeros_like.default, zeros);
+  VK_REGISTER_OP(aten.ones.default, ones);
+  VK_REGISTER_OP(aten.ones_like.default, ones);
 }
 
 } // namespace vkcompute

backends/vulkan/test/op_tests/cases.py

@@ -331,6 +331,25 @@ def get_full_inputs():
     return test_suite
 
 
+@register_test_suite(
+    [
+        "aten.zeros.default",
+        "aten.zeros_like.default",
+        "aten.ones.default",
+        "aten.ones_like.default",
+    ]
+)
+def get_ones_inputs():
+    test_suite = VkTestSuite(
+        [
+            ([S1, S2]),
+            ([M, M1, M2]),
+            ([L, M, M1, M2]),
+        ]
+    )
+    return test_suite
+
+
 @register_test_suite(["aten.select.int", "aten.select_copy.int"])
 def get_select_int_inputs():
     test_suite = VkTestSuite(

backends/vulkan/test/test_vulkan_delegate.py

@@ -963,6 +963,20 @@ def __init__(self):
             def forward(self, x):
                 return torch.full(x.shape, 42.0)
 
+        class ZerosModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return torch.zeros(x.shape)
+
+        class OnesModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return torch.ones(x.shape)
+
         sample_inputs = (torch.randn(size=(2, 3, 4, 5), dtype=torch.float32),)
 
         self.lower_module_and_test_output(
@@ -971,6 +985,18 @@ def forward(self, x):
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
         )
 
+        self.lower_module_and_test_output(
+            ZerosModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
+        self.lower_module_and_test_output(
+            OnesModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
     def test_vulkan_backend_full_like(self):
         class FullLikeModule(torch.nn.Module):
             def __init__(self):
@@ -979,6 +1005,20 @@ def __init__(self):
             def forward(self, x):
                 return torch.full_like(x, 42.0)
 
+        class ZerosLikeModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return torch.zeros_like(x)
+
+        class OnesLikeModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x):
+                return torch.ones_like(x)
+
         sample_inputs = (torch.randn(size=(2, 3, 4, 5), dtype=torch.float32),)
 
         self.lower_module_and_test_output(
@@ -987,6 +1027,18 @@ def forward(self, x):
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
         )
 
+        self.lower_module_and_test_output(
+            ZerosLikeModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
+        self.lower_module_and_test_output(
+            OnesLikeModule(),
+            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):