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Add support for numpy~=2.0
(#8440)
* Add code * add changeset * add changeset * update requirements.txt * remove np.bool8 * add changeset * type check --------- Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Abubakar Abid <abubakar@huggingface.co>
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.changeset/ripe-ears-tease.md
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5
.changeset/ripe-ears-tease.md
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@ -0,0 +1,5 @@
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---
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"gradio": patch
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---
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fix:Add support for `numpy~=2.0`
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@ -104,6 +104,7 @@ log = logging.getLogger(__name__)
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if TYPE_CHECKING:
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from gradio.blocks import Block
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#########################
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# GENERAL
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#########################
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@ -660,14 +661,17 @@ def _convert(image, dtype, force_copy=False, uniform=False):
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dtype_range = {
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bool: (False, True),
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np.bool_: (False, True),
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np.bool8: (False, True), # type: ignore
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float: (-1, 1),
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np.float_: (-1, 1),
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np.float16: (-1, 1),
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np.float32: (-1, 1),
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np.float64: (-1, 1),
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}
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if hasattr(np, "float_"):
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dtype_range[np.float_] = dtype_range[float] # type: ignore
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if hasattr(np, "bool8"):
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dtype_range[np.bool8] = dtype_range[np.bool_] # type: ignore
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def _dtype_itemsize(itemsize, *dtypes):
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"""Return first of `dtypes` with itemsize greater than `itemsize`
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Parameters
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@ -786,7 +790,12 @@ def _convert(image, dtype, force_copy=False, uniform=False):
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# is a subclass of that type (e.g. `np.floating` will allow
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# `float32` and `float64` arrays through)
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if np.issubdtype(dtype_in, np.obj2sctype(dtype)):
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if hasattr(np, "obj2sctype"):
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is_subdtype = np.issubdtype(dtype_in, np.obj2sctype(dtype))
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else:
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is_subdtype = np.issubdtype(dtype_in, dtypeobj_out.type)
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if is_subdtype:
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if force_copy:
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image = image.copy()
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return image
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@ -9,7 +9,7 @@ importlib_resources>=1.3,<7.0
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Jinja2<4.0
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markupsafe~=2.0
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matplotlib~=3.0
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numpy~=1.0
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numpy>=1.0,<3.0
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orjson~=3.0
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packaging
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pandas>=1.0,<3.0
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