Add cv samples for models with more than 30 subgraphs.

Author: Xreki

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/graph_hash.txt

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+1c86568233f9b834312d9525c485088ea33394123460e0ad7ddb2644d1bc2a7e

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/graph_net.json

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+{
+    "framework": "paddle",
+    "model_name": "Cascade-FasterRCNN-ResNet50-FPN",
+    "num_devices_required": 1,
+    "num_nodes_required": 1
+}

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/input_meta.py

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+class Program_weight_tensor_data_0:
+    name = "data_0"
+    shape = [196192]
+    dtype = "int32"
+    min_val = 0
+    max_val = 196191
+    data = None
+
+
+class Program_weight_tensor_data_1:
+    name = "data_1"
+    shape = []
+    dtype = "int64"
+    data = [253]
+
+
+class Program_weight_tensor_data_2:
+    name = "data_2"
+    shape = [196192]
+    dtype = "int32"
+    min_val = 0
+    max_val = 196415
+    data = None
+
+
+class Program_weight_tensor_data_3:
+    name = "data_3"
+    shape = []
+    dtype = "int64"
+    data = [3]

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/model.py

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+import paddle
+
+
+class GraphModule(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, data_0, data_1, data_2, data_3):
+        # pd_op.full_int_array: (1xi64) <- ()
+        full_int_array_0 = [0]
+
+        # builtin.combine: ([xi64]) <- (xi64)
+        combine_0 = [data_1]
+        del data_1
+
+        # pd_op.stack: (1xi64) <- ([xi64])
+        stack_0 = paddle._C_ops.stack(combine_0, 0)
+        del combine_0
+
+        # pd_op.slice: (-1xi32) <- (196192xi32, 1xi64, 1xi64)
+        slice_0 = paddle._C_ops.slice(data_0, [0], full_int_array_0, stack_0, [-1], [])
+        del data_0, full_int_array_0, stack_0
+
+        # pd_op.full: (1xi32) <- ()
+        full_0 = paddle._C_ops.full(
+            [1], float("0"), paddle.int32, paddle.core.CPUPlace()
+        )
+
+        # pd_op.gather: (-1xi32) <- (196192xi32, -1xi32, 1xi32)
+        gather_0 = paddle._C_ops.gather(data_2, slice_0, full_0)
+        del data_2, full_0, slice_0
+
+        # pd_op.full: (xi64) <- ()
+        full_1 = paddle._C_ops.full(
+            [], float("0"), paddle.int64, paddle.framework._current_expected_place()
+        )
+
+        # pd_op.equal: (xb) <- (xi64, xi64)
+        equal_0 = paddle._C_ops.equal(data_3, full_1)
+        del data_3, full_1
+
+        return equal_0, gather_0

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_0/weight_meta.py

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+

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/graph_hash.txt

@@ -0,0 +1 @@
+00ef08cc89ec8f8051c57321c9dd142e65268c6a6cab8a869a81bcd6f9d10a0d

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/graph_net.json

@@ -0,0 +1,6 @@
+{
+    "framework": "paddle",
+    "model_name": "Cascade-FasterRCNN-ResNet50-FPN",
+    "num_devices_required": 1,
+    "num_nodes_required": 1
+}

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/input_meta.py

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+class Program_weight_tensor_data_0:
+    name = "data_0"
+    shape = [2]
+    dtype = "int32"
+    data = [0, 1]
+
+
+class Program_weight_tensor_data_1:
+    name = "data_1"
+    shape = []
+    dtype = "int64"
+    data = [2]
+
+
+class Program_weight_tensor_data_2:
+    name = "data_2"
+    shape = [2]
+    dtype = "int32"
+    data = [189304, 189448]

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/model.py

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+import paddle
+
+
+class GraphModule(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, data_0, data_1, data_2):
+        # pd_op.full_int_array: (1xi64) <- ()
+        full_int_array_0 = [0]
+
+        # builtin.combine: ([xi64]) <- (xi64)
+        combine_0 = [data_1]
+        del data_1
+
+        # pd_op.stack: (1xi64) <- ([xi64])
+        stack_0 = paddle._C_ops.stack(combine_0, 0)
+        del combine_0
+
+        # pd_op.slice: (-1xi32) <- (-1xi32, 1xi64, 1xi64)
+        slice_0 = paddle._C_ops.slice(data_0, [0], full_int_array_0, stack_0, [-1], [])
+        del data_0, full_int_array_0, stack_0
+
+        # pd_op.full: (1xi32) <- ()
+        full_0 = paddle._C_ops.full(
+            [1], float("0"), paddle.int32, paddle.core.CPUPlace()
+        )
+
+        # pd_op.gather: (-1xi32) <- (-1xi32, -1xi32, 1xi32)
+        gather_0 = paddle._C_ops.gather(data_2, slice_0, full_0)
+        del data_2, full_0, slice_0
+
+        return gather_0

paddle_samples/PaddleX/Cascade-FasterRCNN-ResNet50-FPN/subgraph_1/weight_meta.py

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+