Repository: huggingface/transformers
Pull request: Revert "Update deprecated Jax calls (#35919)"

This reverts commit f0d5b2ff04e1354d32beac70984adcc8100352a0.

# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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      Pull Request section?
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- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

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Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @eustlb
- graph models: @clefourrier

Library:

- flax: @gante and @Rocketknight1
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @Rocketknight1
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

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Changed files:
filename: src/transformers/commands/env.py
patch: @@ -129,7 +129,7 @@ def run(self):
             flax_version = flax.__version__
             jax_version = jax.__version__
             jaxlib_version = jaxlib.__version__
-            jax_backend = jax.default_backend()
+            jax_backend = jax.lib.xla_bridge.get_backend().platform
 
         info = {
             "`transformers` version": version,

filename: src/transformers/models/longt5/modeling_flax_longt5.py
patch: @@ -387,7 +387,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
             relative_buckets += (relative_position > 0) * num_buckets
             relative_position = jnp.abs(relative_position)
         else:
-            relative_position = -jnp.clip(relative_position, max=0)
+            relative_position = -jnp.clip(relative_position, a_max=0)
         # now relative_position is in the range [0, inf)
 
         # half of the buckets are for exact increments in positions
@@ -398,7 +398,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
         relative_position_if_large = max_exact + (
             jnp.log(relative_position / max_exact) / jnp.log(max_distance / max_exact) * (num_buckets - max_exact)
         )
-        relative_position_if_large = jnp.clip(relative_position_if_large, max=num_buckets - 1)
+        relative_position_if_large = jnp.clip(relative_position_if_large, a_max=num_buckets - 1)
 
         relative_buckets += jnp.where(is_small, relative_position, relative_position_if_large)
 
@@ -672,7 +672,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
             relative_buckets += (relative_position > 0) * num_buckets
             relative_position = jnp.abs(relative_position)
         else:
-            relative_position = -jnp.clip(relative_position, max=0)
+            relative_position = -jnp.clip(relative_position, a_max=0)
         # now relative_position is in the range [0, inf)
 
         # half of the buckets are for exact increments in positions
@@ -683,7 +683,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
         relative_position_if_large = max_exact + (
             jnp.log(relative_position / max_exact) / jnp.log(max_distance / max_exact) * (num_buckets - max_exact)
         )
-        relative_position_if_large = jnp.clip(relative_position_if_large, max=num_buckets - 1)
+        relative_position_if_large = jnp.clip(relative_position_if_large, a_max=num_buckets - 1)
 
         relative_buckets += jnp.where(is_small, relative_position, relative_position_if_large)
 
@@ -895,7 +895,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
             relative_buckets += (relative_position > 0) * num_buckets
             relative_position = jnp.abs(relative_position)
         else:
-            relative_position = -jnp.clip(relative_position, max=0)
+            relative_position = -jnp.clip(relative_position, a_max=0)
         # now relative_position is in the range [0, inf)
 
         # half of the buckets are for exact increments in positions
@@ -906,7 +906,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
         relative_position_if_large = max_exact + (
             jnp.log(relative_position / max_exact) / jnp.log(max_distance / max_exact) * (num_buckets - max_exact)
         )
-        relative_position_if_large = jnp.clip(relative_position_if_large, max=num_buckets - 1)
+        relative_position_if_large = jnp.clip(relative_position_if_large, a_max=num_buckets - 1)
 
         relative_buckets += jnp.where(is_small, relative_position, relative_position_if_large)
 

filename: src/transformers/models/t5/modeling_flax_t5.py
patch: @@ -247,7 +247,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
             relative_buckets += (relative_position > 0) * num_buckets
             relative_position = jnp.abs(relative_position)
         else:
-            relative_position = -jnp.clip(relative_position, max=0)
+            relative_position = -jnp.clip(relative_position, a_max=0)
         # now relative_position is in the range [0, inf)
 
         # half of the buckets are for exact increments in positions
@@ -258,7 +258,7 @@ def _relative_position_bucket(relative_position, bidirectional=True, num_buckets
         relative_position_if_large = max_exact + (
             jnp.log(relative_position / max_exact) / jnp.log(max_distance / max_exact) * (num_buckets - max_exact)
         )
-        relative_position_if_large = jnp.clip(relative_position_if_large, max=num_buckets - 1)
+        relative_position_if_large = jnp.clip(relative_position_if_large, a_max=num_buckets - 1)
 
         relative_buckets += jnp.where(is_small, relative_position, relative_position_if_large)