fix block_from_array for torch array backend (metatensor-core)

python/metatensor-operations/metatensor/operations/block_from_array.py

@@ -1,5 +1,15 @@
+import numpy as np
+
 from . import _dispatch
-from ._classes import Labels, TensorBlock
+from ._classes import Labels, TensorBlock, check_isinstance, torch_jit_is_scripting
+
+
+try:
+ import torch
+
+ HAS_TORCH = True
+except ImportError:
+ HAS_TORCH = False
 
 
 def block_from_array(array) -> TensorBlock:
@@ -49,22 +59,41 @@ def block_from_array(array) -> TensorBlock:
  must have at least two dimensions. Too few provided: {n_dimensions}"
  )
 
+ if torch_jit_is_scripting():
+ # for metatensor-torch the array backend is always torch
+ labels_array_like = torch.empty(0)
+ else:
+ # This will return true only if we are using metatensor-torch
+ # please refer to function definition in files
+ # metatensor-core python/metatensor-operations/metatensor/operations/_classes.py
+ # metatensor-torch python/metatensor-torch/metatensor/torch/operations.py
+ if check_isinstance(None, Labels):
+ # for metatensor-torch the array backend is always torch
+ labels_array_like = torch.empty(0)
+ else:
+ # for metatensor-core the array backend is always numpy
+ labels_array_like = np.empty(0)
+
  samples = Labels(
  names=["sample"],
- values=_dispatch.int_array_like(list(range(shape[0])), array).reshape(-1, 1),
+ values=_dispatch.int_array_like(
+ list(range(shape[0])), labels_array_like
+ ).reshape(-1, 1),
  )
  components = [
  Labels(
  names=[f"component_{component_index+1}"],
- values=_dispatch.int_array_like(list(range(axis_size)), array).reshape(
- -1, 1
- ),
+ values=_dispatch.int_array_like(
+ list(range(axis_size)), labels_array_like
+ ).reshape(-1, 1),
  )
  for component_index, axis_size in enumerate(shape[1:-1])
  ]
  properties = Labels(
  names=["property"],
- values=_dispatch.int_array_like(list(range(shape[-1])), array).reshape(-1, 1),
+ values=_dispatch.int_array_like(
+ list(range(shape[-1])), labels_array_like
+ ).reshape(-1, 1),
  )
 
  device = _dispatch.get_device(array)