[Add] paddle models

Author: hxzd5568

paddle_samples/vision-model/ResNet18/graph_net.json renamed to paddle_samples/AutoEncoder_ad/graph_net.json

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+class Program_weight_tensor_data_0:
+    name = "input0"
+    shape = [16, 2, 96]
+    dtype = "float32"
+    data = None

paddle_samples/AutoEncoder_ad/input_meta.py

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+import paddle
+
+
+class GraphModule(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(
+        self,
+        input0: paddle.Tensor,
+        t0: paddle.Tensor,
+        t1: paddle.Tensor,
+        t2: paddle.Tensor,
+    ):
+        t3 = None
+        # pd_op.matmul: (16x2x32xf32) <- (16x2x96xf32, 96x32xf32)
+        t4 = paddle._C_ops.matmul(input0, t0, False, False)
+        del input0, t0
+
+        # pd_op.add: (16x2x32xf32) <- (16x2x32xf32, 32xf32)
+        t5 = paddle._C_ops.add(t4, t1)
+        del t1
+
+        # pd_op.relu: (16x2x32xf32) <- (16x2x32xf32)
+        t6 = paddle._C_ops.relu(t5)
+        del t5
+
+        # pd_op.full: (1xf32) <- ()
+        t7 = paddle._C_ops.full(
+            [1], float("0.2"), paddle.float32, paddle.core.CPUPlace()
+        )
+
+        # pd_op.dropout: (16x2x32xf32, 16x2x32xui8) <- (16x2x32xf32, None, 1xf32)
+        t8, t9 = (lambda x, f: f(x))(
+            paddle._C_ops.dropout(t6, None, t7, False, "upscale_in_train", 0, False),
+            lambda out: out if isinstance(out, (list, tuple)) else (out, None),
+        )
+
+        # pd_op.matmul: (16x2x16xf32) <- (16x2x32xf32, 32x16xf32)
+        t10 = paddle._C_ops.matmul(t8, t2, False, False)
+        del t2
+
+        return t4, t6, t7, t8, t9, t10

paddle_samples/AutoEncoder_ad/model.py

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+class Program_weight_tensor_parameter_3:
+    name = "t0"
+    shape = [96, 32]
+    dtype = "float32"
+    data = None
+
+
+class Program_weight_tensor_parameter_2:
+    name = "t1"
+    shape = [32]
+    dtype = "float32"
+    data = None
+
+
+class Program_weight_tensor_parameter_1:
+    name = "t2"
+    shape = [32, 16]
+    dtype = "float32"
+    data = None

paddle_samples/AutoEncoder_ad/weight_meta.py

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+{
+    "framework": "paddle",
+    "num_devices_required": 1,
+    "num_nodes_required": 1
+}

paddle_samples/CLIP_vit_base_patch16_224/graph_net.json

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+class Program_weight_tensor_data_0:
+    name = "input0"
+    shape = [32, 3, 224, 224]
+    dtype = "float32"
+    data = None
+
+
+class Program_weight_tensor_data_1:
+    name = "input1"
+    shape = [1, 1, 768]
+    dtype = "float32"
+    data = None
+
+
+class Program_weight_tensor_data_2:
+    name = "input2"
+    shape = [1, 197, 768]
+    dtype = "float32"
+    data = None