[IPU] support depthwise_conv2d ops (#45234)

* support depthwise_conv2d ops
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>

* fix duplicate name
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>

paddle/fluid/platform/device/ipu/popart_canonicalization/activation_ops.cc

@@ -138,6 +138,10 @@ Node *brelu_handler(Graph *graph, Node *node) {
 
 Node *gelu_handler(Graph *graph, Node *node) {
   auto *op = node->Op();
+  // In case of the Op has no `approximate` attr.
+  if (!op->HasAttr("approximate")) {
+    return activation_op_handler(graph, node, "popart_gelu_v2");
+  }
   auto approximate_ = PADDLE_GET_CONST(bool, op->GetAttr("approximate"));
   if (approximate_) {
     return activation_op_handler(graph, node, "popart_gelu_v2");

paddle/fluid/platform/device/ipu/popart_canonicalization/nn_ops.cc

@@ -824,6 +824,14 @@ Node *pad_handler(Graph *graph, Node *node) {
                       {{"mode", mode}});
 }
 
+Node *depthwise_conv2d_handler(Graph *graph, Node *node) {
+  return conv2d_handler(graph, node);
+}
+
+Node *depthwise_conv2d_transpose_handler(Graph *graph, Node *node) {
+  return conv2d_transpose_handler(graph, node);
+}
+
 }  // namespace
 }  // namespace ipu
 }  // namespace platform
@@ -846,3 +854,6 @@ REGISTER_HANDLER(linear_interp_v2, linear_interp_v2_handler);
 REGISTER_HANDLER(trilinear_interp_v2, trilinear_interp_v2_handler);
 REGISTER_HANDLER(data_norm, data_norm_handler);
 REGISTER_HANDLER(pad3d, pad_handler);
+REGISTER_HANDLER(depthwise_conv2d, depthwise_conv2d_handler);
+REGISTER_HANDLER(depthwise_conv2d_transpose,
+                 depthwise_conv2d_transpose_handler);

python/paddle/fluid/tests/unittests/ipu/test_conv2d_transpose_op_ipu.py

@@ -150,11 +150,43 @@ class TestCase10(TestBase):
 
 class TestCase11(TestBase):
 
-    # Depthwise conv2d transpose
     def set_op_attrs(self):
         super().set_op_attrs()
         self.attrs['groups'] = 3
 
 
+# depthwise_conv2d_transpose Op
+class TestCase12(TestBase):
+
+    def set_feed(self):
+        data = np.random.uniform(size=[1, 3, 10, 10])
+        weight = np.random.uniform(size=[3, 1, 3, 3])
+        self.feed_fp32 = {
+            'in_0': data.astype(np.float32),
+            'in_1': weight.astype(np.float32)
+        }
+        self.feed_fp16 = {
+            'in_0': data.astype(np.float16),
+            'in_1': weight.astype(np.float16)
+        }
+        self.feed_shape = [x.shape for x in self.feed_fp32.values()]
+        self.feed_list = list(self.feed_fp32.keys())
+
+    def set_op_attrs(self):
+        self.attrs = {}
+        self.attrs['groups'] = 3
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        weight = paddle.static.data(name=self.feed_list[1],
+                                    shape=self.feed_shape[1],
+                                    dtype='float32')
+        x = paddle.nn.functional.conv2d_transpose(x, weight, **self.attrs)
+        self.fetch_list = [x.name]
+
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_conv_op_ipu.py

@@ -133,5 +133,38 @@ class TestCase8(TestBase):
         self.attrs['padding'] = [1, 2, 2, 3]
 
 
+# depthwise_conv2d Op
+class TestCase9(TestBase):
+
+    def set_feed(self):
+        data = np.random.uniform(size=[1, 3, 10, 10])
+        weight = np.random.uniform(size=[3, 1, 3, 3])
+        self.feed_fp32 = {
+            'in_0': data.astype(np.float32),
+            'in_1': weight.astype(np.float32)
+        }
+        self.feed_fp16 = {
+            'in_0': data.astype(np.float16),
+            'in_1': weight.astype(np.float16)
+        }
+        self.feed_shape = [x.shape for x in self.feed_fp32.values()]
+        self.feed_list = list(self.feed_fp32.keys())
+
+    def set_op_attrs(self):
+        self.attrs = {}
+        self.attrs['groups'] = 3
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        weight = paddle.static.data(name=self.feed_list[1],
+                                    shape=self.feed_shape[1],
+                                    dtype='float32')
+        x = paddle.nn.functional.conv2d(x, weight, **self.attrs)
+        self.fetch_list = [x.name]
+
+
 if __name__ == "__main__":
     unittest.main()