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Un-deprecate timeout arg in pipelines (#34382)

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* Un-deprecate timeout

* Put "timeout" on the allowed list

* make fixup
This commit is contained in:
Matt
2024-10-29 18:45:14 +00:00
committed by GitHub
parent e4449bb790
commit 9bee9ff5db
7 changed files with 27 additions and 23 deletions
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7
src/transformers/pipelines/depth_estimation.py
View File

@@ -1,4 +1,3 @@
import warnings
from typing import List, Union from typing import List, Union
from ..utils import ( from ..utils import (
@@ -72,6 +71,9 @@ class DepthEstimationPipeline(Pipeline):
A dictionary of argument names to parameter values, to control pipeline behaviour. A dictionary of argument names to parameter values, to control pipeline behaviour.
The only parameter available right now is `timeout`, which is the length of time, in seconds, The only parameter available right now is `timeout`, which is the length of time, in seconds,
that the pipeline should wait before giving up on trying to download an image. that the pipeline should wait before giving up on trying to download an image.
timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
the call may block forever.
Return: Return:
A dictionary or a list of dictionaries containing result. If the input is a single image, will return a A dictionary or a list of dictionaries containing result. If the input is a single image, will return a
@@ -93,9 +95,6 @@ class DepthEstimationPipeline(Pipeline):
def _sanitize_parameters(self, timeout=None, parameters=None, **kwargs): def _sanitize_parameters(self, timeout=None, parameters=None, **kwargs):
preprocess_params = {} preprocess_params = {}
if timeout is not None: if timeout is not None:
warnings.warn(
"The `timeout` argument is deprecated and will be removed in version 5 of Transformers", FutureWarning
)
preprocess_params["timeout"] = timeout preprocess_params["timeout"] = timeout
if isinstance(parameters, dict) and "timeout" in parameters: if isinstance(parameters, dict) and "timeout" in parameters:
preprocess_params["timeout"] = parameters["timeout"] preprocess_params["timeout"] = parameters["timeout"]

7
src/transformers/pipelines/image_classification.py
View File

@@ -11,7 +11,6 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
import warnings
from typing import List, Union from typing import List, Union
import numpy as np import numpy as np
@@ -113,9 +112,6 @@ class ImageClassificationPipeline(Pipeline):
def _sanitize_parameters(self, top_k=None, function_to_apply=None, timeout=None): def _sanitize_parameters(self, top_k=None, function_to_apply=None, timeout=None):
preprocess_params = {} preprocess_params = {}
if timeout is not None: if timeout is not None:
warnings.warn(
"The `timeout` argument is deprecated and will be removed in version 5 of Transformers", FutureWarning
)
preprocess_params["timeout"] = timeout preprocess_params["timeout"] = timeout
postprocess_params = {} postprocess_params = {}
if top_k is not None: if top_k is not None:
@@ -159,6 +155,9 @@ class ImageClassificationPipeline(Pipeline):
top_k (`int`, *optional*, defaults to 5): top_k (`int`, *optional*, defaults to 5):
The number of top labels that will be returned by the pipeline. If the provided number is higher than The number of top labels that will be returned by the pipeline. If the provided number is higher than
the number of labels available in the model configuration, it will default to the number of labels. the number of labels available in the model configuration, it will default to the number of labels.
timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
the call may block forever.
Return: Return:
A dictionary or a list of dictionaries containing result. If the input is a single image, will return a A dictionary or a list of dictionaries containing result. If the input is a single image, will return a

7
src/transformers/pipelines/image_segmentation.py
View File

@@ -1,4 +1,3 @@
import warnings
from typing import Any, Dict, List, Union from typing import Any, Dict, List, Union
import numpy as np import numpy as np
@@ -91,9 +90,6 @@ class ImageSegmentationPipeline(Pipeline):
if "overlap_mask_area_threshold" in kwargs: if "overlap_mask_area_threshold" in kwargs:
postprocess_kwargs["overlap_mask_area_threshold"] = kwargs["overlap_mask_area_threshold"] postprocess_kwargs["overlap_mask_area_threshold"] = kwargs["overlap_mask_area_threshold"]
if "timeout" in kwargs: if "timeout" in kwargs:
warnings.warn(
"The `timeout` argument is deprecated and will be removed in version 5 of Transformers", FutureWarning
)
preprocess_kwargs["timeout"] = kwargs["timeout"] preprocess_kwargs["timeout"] = kwargs["timeout"]
return preprocess_kwargs, {}, postprocess_kwargs return preprocess_kwargs, {}, postprocess_kwargs
@@ -122,6 +118,9 @@ class ImageSegmentationPipeline(Pipeline):
Threshold to use when turning the predicted masks into binary values. Threshold to use when turning the predicted masks into binary values.
overlap_mask_area_threshold (`float`, *optional*, defaults to 0.5): overlap_mask_area_threshold (`float`, *optional*, defaults to 0.5):
Mask overlap threshold to eliminate small, disconnected segments. Mask overlap threshold to eliminate small, disconnected segments.
timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
the call may block forever.
Return: Return:
A dictionary or a list of dictionaries containing the result. If the input is a single image, will return a A dictionary or a list of dictionaries containing the result. If the input is a single image, will return a

8
src/transformers/pipelines/image_to_text.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
import warnings
from typing import List, Union from typing import List, Union
from ..utils import ( from ..utils import (
@@ -81,9 +80,6 @@ class ImageToTextPipeline(Pipeline):
if prompt is not None: if prompt is not None:
preprocess_params["prompt"] = prompt preprocess_params["prompt"] = prompt
if timeout is not None: if timeout is not None:
warnings.warn(
"The `timeout` argument is deprecated and will be removed in version 5 of Transformers", FutureWarning
)
preprocess_params["timeout"] = timeout preprocess_params["timeout"] = timeout
if max_new_tokens is not None: if max_new_tokens is not None:
@@ -118,6 +114,10 @@ class ImageToTextPipeline(Pipeline):
generate_kwargs (`Dict`, *optional*): generate_kwargs (`Dict`, *optional*):
Pass it to send all of these arguments directly to `generate` allowing full control of this function. Pass it to send all of these arguments directly to `generate` allowing full control of this function.
timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
the call may block forever.
Return: Return:
A list or a list of list of `dict`: Each result comes as a dictionary with the following key: A list or a list of list of `dict`: Each result comes as a dictionary with the following key:

7
src/transformers/pipelines/object_detection.py
View File

@@ -1,4 +1,3 @@
import warnings
from typing import Any, Dict, List, Union from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
@@ -64,9 +63,6 @@ class ObjectDetectionPipeline(Pipeline):
def _sanitize_parameters(self, **kwargs): def _sanitize_parameters(self, **kwargs):
preprocess_params = {} preprocess_params = {}
if "timeout" in kwargs: if "timeout" in kwargs:
warnings.warn(
"The `timeout` argument is deprecated and will be removed in version 5 of Transformers", FutureWarning
)
preprocess_params["timeout"] = kwargs["timeout"] preprocess_params["timeout"] = kwargs["timeout"]
postprocess_kwargs = {} postprocess_kwargs = {}
if "threshold" in kwargs: if "threshold" in kwargs:
@@ -89,6 +85,9 @@ class ObjectDetectionPipeline(Pipeline):
same format: all as HTTP(S) links, all as local paths, or all as PIL images. same format: all as HTTP(S) links, all as local paths, or all as PIL images.
threshold (`float`, *optional*, defaults to 0.5): threshold (`float`, *optional*, defaults to 0.5):
The probability necessary to make a prediction. The probability necessary to make a prediction.
timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
the call may block forever.
Return: Return:
A list of dictionaries or a list of list of dictionaries containing the result. If the input is a single A list of dictionaries or a list of list of dictionaries containing the result. If the input is a single

7
src/transformers/pipelines/zero_shot_image_classification.py
View File

@@ -94,6 +94,10 @@ class ZeroShotImageClassificationPipeline(Pipeline):
replacing the placeholder with the candidate_labels. Pass "{}" if *candidate_labels* are replacing the placeholder with the candidate_labels. Pass "{}" if *candidate_labels* are
already formatted. already formatted.
timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
the call may block forever.
Return: Return:
A list of dictionaries containing one entry per proposed label. Each dictionary contains the A list of dictionaries containing one entry per proposed label. Each dictionary contains the
following keys: following keys:
@@ -113,9 +117,6 @@ class ZeroShotImageClassificationPipeline(Pipeline):
if "candidate_labels" in kwargs: if "candidate_labels" in kwargs:
preprocess_params["candidate_labels"] = kwargs["candidate_labels"] preprocess_params["candidate_labels"] = kwargs["candidate_labels"]
if "timeout" in kwargs: if "timeout" in kwargs:
warnings.warn(
"The `timeout` argument is deprecated and will be removed in version 5 of Transformers", FutureWarning
)
preprocess_params["timeout"] = kwargs["timeout"] preprocess_params["timeout"] = kwargs["timeout"]
if "hypothesis_template" in kwargs: if "hypothesis_template" in kwargs:
preprocess_params["hypothesis_template"] = kwargs["hypothesis_template"] preprocess_params["hypothesis_template"] = kwargs["hypothesis_template"]

7
tests/test_pipeline_mixin.py
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@@ -916,6 +916,8 @@ def parse_args_from_docstring_by_indentation(docstring):
def compare_pipeline_args_to_hub_spec(pipeline_class, hub_spec): def compare_pipeline_args_to_hub_spec(pipeline_class, hub_spec):
ALLOWED_TRANSFORMERS_ONLY_ARGS = ["timeout"]
docstring = inspect.getdoc(pipeline_class.__call__).strip() docstring = inspect.getdoc(pipeline_class.__call__).strip()
docstring_args = set(parse_args_from_docstring_by_indentation(docstring)) docstring_args = set(parse_args_from_docstring_by_indentation(docstring))
hub_args = set(get_arg_names_from_hub_spec(hub_spec)) hub_args = set(get_arg_names_from_hub_spec(hub_spec))
@@ -933,6 +935,11 @@ def compare_pipeline_args_to_hub_spec(pipeline_class, hub_spec):
hub_args.remove(js_generate_args[0]) hub_args.remove(js_generate_args[0])
docstring_args.remove(docstring_generate_args[0]) docstring_args.remove(docstring_generate_args[0])
# Special casing 2: We permit some transformers-only arguments that don't affect pipeline output
for arg in ALLOWED_TRANSFORMERS_ONLY_ARGS:
if arg in docstring_args and arg not in hub_args:
docstring_args.remove(arg)
if hub_args != docstring_args: if hub_args != docstring_args:
error = [f"{pipeline_class.__name__} differs from JS spec {hub_spec.__name__}"] error = [f"{pipeline_class.__name__} differs from JS spec {hub_spec.__name__}"]
matching_args = hub_args & docstring_args matching_args = hub_args & docstring_args