Un-deprecate timeout arg in pipelines (#34382)

* Un-deprecate timeout

* Put "timeout" on the allowed list

* make fixup

src/transformers/pipelines/depth_estimation.py

@@ -1,4 +1,3 @@
-import warnings
 from typing import List, Union
 
 from ..utils import (
@@ -72,6 +71,9 @@ class DepthEstimationPipeline(Pipeline):
                 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,
                 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:
             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):
         preprocess_params = {}
         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
         if isinstance(parameters, dict) and "timeout" in parameters:
             preprocess_params["timeout"] = parameters["timeout"]

src/transformers/pipelines/image_classification.py

@@ -11,7 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import warnings
 from typing import List, Union
 
 import numpy as np
@@ -113,9 +112,6 @@ class ImageClassificationPipeline(Pipeline):
     def _sanitize_parameters(self, top_k=None, function_to_apply=None, timeout=None):
         preprocess_params = {}
         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
         postprocess_params = {}
         if top_k is not None:
@@ -159,6 +155,9 @@ class ImageClassificationPipeline(Pipeline):
             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 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:
             A dictionary or a list of dictionaries containing result. If the input is a single image, will return a

src/transformers/pipelines/image_segmentation.py

@@ -1,4 +1,3 @@
-import warnings
 from typing import Any, Dict, List, Union
 
 import numpy as np
@@ -91,9 +90,6 @@ class ImageSegmentationPipeline(Pipeline):
         if "overlap_mask_area_threshold" in kwargs:
             postprocess_kwargs["overlap_mask_area_threshold"] = kwargs["overlap_mask_area_threshold"]
         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"]
 
         return preprocess_kwargs, {}, postprocess_kwargs
@@ -122,6 +118,9 @@ class ImageSegmentationPipeline(Pipeline):
                 Threshold to use when turning the predicted masks into binary values.
             overlap_mask_area_threshold (`float`, *optional*, defaults to 0.5):
                 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:
             A dictionary or a list of dictionaries containing the result. If the input is a single image, will return a

src/transformers/pipelines/image_to_text.py

@@ -13,7 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import warnings
 from typing import List, Union
 
 from ..utils import (
@@ -81,9 +80,6 @@ class ImageToTextPipeline(Pipeline):
         if prompt is not None:
             preprocess_params["prompt"] = prompt
         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
 
         if max_new_tokens is not None:
@@ -118,6 +114,10 @@ class ImageToTextPipeline(Pipeline):
             generate_kwargs (`Dict`, *optional*):
                 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:
             A list or a list of list of `dict`: Each result comes as a dictionary with the following key:
 

src/transformers/pipelines/object_detection.py

@@ -1,4 +1,3 @@
-import warnings
 from typing import Any, Dict, List, Union
 
 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):
         preprocess_params = {}
         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"]
         postprocess_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.
             threshold (`float`, *optional*, defaults to 0.5):
                 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:
             A list of dictionaries or a list of list of dictionaries containing the result. If the input is a single

src/transformers/pipelines/zero_shot_image_classification.py

@@ -94,6 +94,10 @@ class ZeroShotImageClassificationPipeline(Pipeline):
                 replacing the placeholder with the candidate_labels. Pass "{}" if *candidate_labels* are
                 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:
             A list of dictionaries containing one entry per proposed label. Each dictionary contains the
             following keys:
@@ -113,9 +117,6 @@ class ZeroShotImageClassificationPipeline(Pipeline):
         if "candidate_labels" in kwargs:
             preprocess_params["candidate_labels"] = kwargs["candidate_labels"]
         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"]
         if "hypothesis_template" in kwargs:
             preprocess_params["hypothesis_template"] = kwargs["hypothesis_template"]

tests/test_pipeline_mixin.py

@@ -916,6 +916,8 @@ def parse_args_from_docstring_by_indentation(docstring):
 
 
 def compare_pipeline_args_to_hub_spec(pipeline_class, hub_spec):
+    ALLOWED_TRANSFORMERS_ONLY_ARGS = ["timeout"]
+
     docstring = inspect.getdoc(pipeline_class.__call__).strip()
     docstring_args = set(parse_args_from_docstring_by_indentation(docstring))
     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])
         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:
         error = [f"{pipeline_class.__name__} differs from JS spec {hub_spec.__name__}"]
         matching_args = hub_args & docstring_args