Merge branch 'develop' of https://github.com/PaddlePaddle/GraphNet into cosyvoice_part1

Author: ooooo-create

graph_net/paddle/utils.py

@@ -132,9 +132,9 @@ def convert_meta_classes_to_tensors(file_path):
             if isinstance(attrs.get("data"), str):
                 raise ValueError("Unimplemented")
             else:
-                data_value = paddle.tensor(attrs["data"], dtype=data_type).reshape(
-                    attrs.get("shape"), []
-                )
+                data_value = paddle.to_tensor(
+                    attrs.get("data"), dtype=data_type
+                ).reshape(attrs.get("shape"), [])
         yield {
             "info": {
                 "shape": attrs.get("shape", []),
@@ -170,4 +170,4 @@ def replay_tensor(info):
     if "data" in info and info["data"] is not None:
         return info["data"].to(device)
 
-    return paddle.randn(shape).to(dtype).to(device) * std * 1e-3 + 1e-2
+    return (paddle.randn(shape).cast(dtype).to(device) * std * 1e-3 + 1e-2).cast(dtype)

graph_net/paddle/validate.py

@@ -12,6 +12,7 @@
 import graph_net
 import os
 import re
+import paddle
 
 
 def load_class_from_file(file_path: str, class_name: str):
@@ -68,7 +69,15 @@ def main(args):
     y = model(**state_dict)[0]
 
     print(np.argmin(y), np.argmax(y))
-    print(y.shape)
+    if isinstance(y, paddle.Tensor):
+        print(y.shape)
+    elif (isinstance(y, list) or isinstance(y, tuple)) and all(
+        isinstance(obj, paddle.Tensor) for obj in y
+    ):
+        # list of paddle.Tensor
+        print(y[0].shape)
+    else:
+        raise ValueError("Illegal return value.")
 
     if not args.no_check_redundancy:
         print("Check redundancy ...")

graph_net/torch/utils.py

@@ -265,4 +265,6 @@ def replay_tensor(info):
     std = info["info"]["std"]
     if "data" in info and info["data"] is not None:
         return info["data"].to(device)
+    if dtype is torch.bool:
+        return (torch.randn(size=shape) > 0.5).to(dtype).to(device)
     return torch.randn(size=shape).to(dtype).to(device) * std * 0.2 + mean

samples/mmseg/DeiT_B/graph_hash.txt

@@ -0,0 +1 @@
+dda77fde4b537ec1947ab7ca772a7e22148567438f51c8140c4ad22659333583

samples/mmseg/DeiT_B/graph_net.json

@@ -0,0 +1,6 @@
+{
+    "framework": "torch",
+    "num_devices_required": 1,
+    "num_nodes_required": 1,
+    "dynamic": false
+}