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Reshape arrays rather than setting shape on them. by shubhxho · Pull Request #548 · google-deepmind/dm_control · GitHub

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2 changes: 1 addition & 1 deletion dm_control/mujoco/index.py
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode characters
Original file line number Diff line number Diff line change
Expand Up @@ -378,7 +378,7 @@ def convert_key_item(self, key_item):
key_item = np.array([self._names_to_offsets[util.to_native_string(k)]
for k in key_item.flat])
# Ensure the output shape is the same as that of the input.
key_item.shape = original_shape
key_item = key_item.reshape(original_shape)

return key_item

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5 changes: 3 additions & 2 deletions dm_control/mujoco/index_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -347,8 +347,9 @@ def testReadWrite_(self, field):
# Write unique values to the FieldIndexer and read them back again.
# Don't write to non-float fields since these might contain pointers.
if np.issubdtype(old_contents.dtype, np.floating):
new_contents = np.arange(old_contents.size, dtype=old_contents.dtype)
new_contents.shape = old_contents.shape
new_contents = np.arange(
old_contents.size, dtype=old_contents.dtype
).reshape(old_contents.shape)
field[:] = new_contents
np.testing.assert_array_equal(new_contents, field[:])

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5 changes: 3 additions & 2 deletions dm_control/mujoco/wrapper/core_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -552,8 +552,9 @@ def _write_unique_values(self, attr_name, target_array):
elif (attr_name != "stack"
and not np.issubdtype(target_array.dtype, np.integer)
and not np.issubdtype(target_array.dtype, np.bool_)):
new_contents = np.arange(target_array.size, dtype=target_array.dtype)
new_contents.shape = target_array.shape
new_contents = np.arange(
target_array.size, dtype=target_array.dtype
).reshape(target_array.shape)
target_array[:] = new_contents
np.testing.assert_array_equal(new_contents, target_array[:])

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