[pycharm] PY-80607 Tables(Jupyter, DataView): support requires_grad case

(cherry picked from commit 8f8be0cc80f3473e6fabd2f9cf9034a2103cdbfd)

GitOrigin-RevId: cc10b1639b4be14201e2a7a89655146e4e4bbead

python/helpers/pydev/_pydevd_bundle/pydevd_thrift.py

@@ -420,17 +420,26 @@ def array_to_thrift_struct(array, name, roffset, coffset, rows, cols, format):
     return array_chunk
 
 
-def tensor_to_thrift_struct(tensor, name, roffset, coffset, rows, cols, format):
+def tf_to_thrift_struct(tensor, name, roffset, coffset, rows, cols, format):
     try:
         return array_to_thrift_struct(tensor.numpy(), name, roffset, coffset, rows, cols, format)
     except TypeError:
         return array_to_thrift_struct(tensor.to_dense().numpy(), name, roffset, coffset, rows, cols, format)
 
 
-def sparse_tensor_to_thrift_struct(tensor, name, roffset, coffset, rows, cols, format):
+def torch_to_thrift_struct(tensor, name, roffset, coffset, rows, cols, format):
+    try:
+        if tensor.requires_grad:
+            tensor = tensor.detach()
+        return array_to_thrift_struct(tensor.numpy(), name, roffset, coffset, rows, cols, format)
+    except TypeError:
+        return array_to_thrift_struct(tensor.to_dense().numpy(), name, roffset, coffset, rows, cols, format)
+
+
+def tf_sparse_to_thrift_struct(tensor, name, roffset, coffset, rows, cols, format):
     try:
         import tensorflow as tf
-        return tensor_to_thrift_struct(tf.sparse.to_dense(tf.sparse.reorder(tensor)), name, roffset, coffset, rows, cols, format)
+        return tf_to_thrift_struct(tf.sparse.to_dense(tf.sparse.reorder(tensor)), name, roffset, coffset, rows, cols, format)
     except ImportError:
         pass
 
@@ -646,10 +655,10 @@ def header_data_to_thrift_struct(rows, cols, dtypes, col_bounds, col_to_format,
 TYPE_TO_THRIFT_STRUCT_CONVERTERS = {
     "ndarray": array_to_thrift_struct,
     "recarray": array_to_thrift_struct,
-    "EagerTensor": tensor_to_thrift_struct,
-    "ResourceVariable": tensor_to_thrift_struct,
-    "SparseTensor": sparse_tensor_to_thrift_struct,
-    "Tensor": tensor_to_thrift_struct,
+    "EagerTensor": tf_to_thrift_struct,
+    "ResourceVariable": tf_to_thrift_struct,
+    "SparseTensor": tf_sparse_to_thrift_struct,
+    "Tensor": torch_to_thrift_struct,
     "DataFrame": dataframe_to_thrift_struct,
     "Series": dataframe_to_thrift_struct,
     "Dataset": dataset_to_thrift_struct,

python/helpers/pydev/_pydevd_bundle/pydevd_vars.py

@@ -589,17 +589,26 @@ def array_to_xml(array, name, roffset, coffset, rows, cols, format):
     return xml
 
 
-def tensor_to_xml(tensor, name, roffset, coffset, rows, cols, format):
+def tf_to_xml(tensor, name, roffset, coffset, rows, cols, format):
     try:
         return array_to_xml(tensor.numpy(), name, roffset, coffset, rows, cols, format)
     except TypeError:
         return array_to_xml(tensor.to_dense().numpy(), name, roffset, coffset, rows, cols, format)
 
 
-def sparse_tensor_to_xml(tensor, name, roffset, coffset, rows, cols, format):
+def torch_to_xml(tensor, name, roffset, coffset, rows, cols, format):
+    try:
+        if tensor.requires_grad:
+            tensor = tensor.detach()
+        return array_to_xml(tensor.numpy(), name, roffset, coffset, rows, cols, format)
+    except TypeError:
+        return array_to_xml(tensor.to_dense().numpy(), name, roffset, coffset, rows, cols, format)
+
+
+def tf_sparse_to_xml(tensor, name, roffset, coffset, rows, cols, format):
     try:
         import tensorflow as tf
-        return tensor_to_xml(tf.sparse.to_dense(tf.sparse.reorder(tensor)), name, roffset, coffset, rows, cols, format)
+        return tf_to_xml(tf.sparse.to_dense(tf.sparse.reorder(tensor)), name, roffset, coffset, rows, cols, format)
     except ImportError:
         pass
 
@@ -861,10 +870,10 @@ TYPE_TO_XML_CONVERTERS = {
     "Series": dataframe_to_xml,
     "GeoDataFrame": dataframe_to_xml,
     "GeoSeries": dataframe_to_xml,
-    "EagerTensor": tensor_to_xml,
-    "ResourceVariable": tensor_to_xml,
-    "SparseTensor": sparse_tensor_to_xml,
-    "Tensor": tensor_to_xml,
+    "EagerTensor": tf_to_xml,
+    "ResourceVariable": tf_to_xml,
+    "SparseTensor": tf_sparse_to_xml,
+    "Tensor": torch_to_xml,
     "Dataset": dataset_to_xml
 }
 

python/helpers/pydev/_pydevd_bundle/tables/images/pydevd_numpy_based_image.py

@@ -31,6 +31,14 @@ def create_image(arr):
                 arr_to_convert = tf.sparse.to_dense(tf.sparse.reorder(arr_to_convert))
         except ImportError:
             pass
+        try:
+            import torch
+            if isinstance(arr_to_convert, torch.Tensor):
+                if arr_to_convert.requires_grad:
+                    arr_to_convert = arr_to_convert.detach()
+                arr_to_convert = arr_to_convert.to_dense()
+        except Exception:
+            pass
 
         arr_to_convert = arr_to_convert.numpy()
         arr_to_convert = np.where(arr_to_convert == None, 0, arr_to_convert)

python/helpers/pydev/_pydevd_bundle/tables/pydevd_numpy_based.py

@@ -287,6 +287,8 @@ def __create_table(command, start_index=None, end_index=None, format=None):
     try:
         import torch
         if isinstance(np_array, torch.Tensor):
+            if np_array.requires_grad:
+                np_array = np_array.detach()
             np_array = np_array.to_dense()
     except Exception:
         pass