Generate: FLAX infers pad token in its absence and has functional example

src/transformers/generation/flax_utils.py

@@ -305,10 +305,10 @@ def generate(
         >>> model = FlaxAutoModelForCausalLM.from_pretrained("distilgpt2")
         >>> input_context = "The dog"
         >>> # encode input context
-        >>> input_ids = tokenizer(input_context, return_tensors="np").input_ids
+        >>> inputs = tokenizer(input_context, return_tensors="np")
         >>> # generate candidates using sampling
-        >>> outputs = model.generate(input_ids=input_ids, max_length=20, top_k=30, do_sample=True)
-        >>> tokenizer.batch_decode(outputs, skip_special_tokens=True)
+        >>> outputs = model.generate(**inputs, max_length=20, top_k=30, do_sample=True)
+        >>> tokenizer.batch_decode(outputs.sequences, skip_special_tokens=True)
         ```"""
         # Validate the `.generate()` call
         self._validate_model_class()
@@ -323,6 +323,17 @@ def generate(
         )
         prng_key = prng_key if prng_key is not None else jax.random.PRNGKey(0)
 
+        if pad_token_id is None and eos_token_id is not None:
+            if model_kwargs.get("attention_mask") is None:
+                logger.warning(
+                    "The attention mask and the pad token id were not set. As a consequence, you may observe "
+                    "unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results."
+                )
+            if isinstance(eos_token_id, list):
+                eos_token_id = eos_token_id[0]
+            logger.warning(f"Setting `pad_token_id` to `eos_token_id`:{eos_token_id} for open-end generation.")
+            pad_token_id = eos_token_id
+
         if decoder_start_token_id is None and self.config.is_encoder_decoder:
             raise ValueError("`decoder_start_token_id` has to be defined for encoder-decoder generation.")
 
@@ -525,8 +536,8 @@ def _greedy_search(
 
         batch_size, cur_len = input_ids.shape
 
-        eos_token_id = jnp.array(eos_token_id)
-        pad_token_id = jnp.array(pad_token_id)
+        eos_token_id = jnp.array(eos_token_id, dtype=jnp.int32 if eos_token_id is not None else None)
+        pad_token_id = jnp.array(pad_token_id, dtype=jnp.int32)
         cur_len = jnp.array(cur_len)
 
         # per batch-item holding current token in loop.
@@ -614,8 +625,8 @@ def _sample(
 
         batch_size, cur_len = input_ids.shape
 
-        eos_token_id = jnp.array(eos_token_id)
-        pad_token_id = jnp.array(pad_token_id)
+        eos_token_id = jnp.array(eos_token_id, dtype=jnp.int32 if eos_token_id is not None else None)
+        pad_token_id = jnp.array(pad_token_id, dtype=jnp.int32)
         cur_len = jnp.array(cur_len)
 
         # per batch-item holding current token in loop.
@@ -748,8 +759,8 @@ def gather_fn(tensor):
 
         batch_size, num_beams, cur_len = input_ids.shape
 
-        eos_token_id = jnp.array(eos_token_id)
-        pad_token_id = jnp.array(pad_token_id)
+        eos_token_id = jnp.array(eos_token_id, dtype=jnp.int32 if eos_token_id is not None else None)
+        pad_token_id = jnp.array(pad_token_id, dtype=jnp.int32)
         cur_len = jnp.array(cur_len)
 
         # per batch,beam-item holding current token in loop.

src/transformers/generation/tf_utils.py

@@ -702,11 +702,11 @@ def generate(
                     "The attention mask and the pad token id were not set. As a consequence, you may observe "
                     "unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results."
                 )
-            logger.warning(
-                f"Setting `pad_token_id` to {generation_config.eos_token_id} (first `eos_token_id`) to generate"
-                " sequence"
-            )
-            generation_config.pad_token_id = generation_config.eos_token_id
+            eos_token_id = generation_config.eos_token_id
+            if isinstance(eos_token_id, list):
+                eos_token_id = eos_token_id[0]
+            logger.warning(f"Setting `pad_token_id` to `eos_token_id`:{eos_token_id} for open-end generation.")
+            generation_config.pad_token_id = eos_token_id
 
         use_xla = not tf.executing_eagerly()
         if use_xla and not self.supports_xla_generation:

utils/documentation_tests.txt

@@ -13,6 +13,7 @@ docs/source/en/model_doc/tapex.mdx
 docs/source/en/model_doc/donut.mdx
 docs/source/en/model_doc/encoder-decoder.mdx
 src/transformers/generation/configuration_utils.py
+src/transformers/generation/flax_utils.py
 src/transformers/generation/tf_utils.py
 src/transformers/generation/utils.py
 src/transformers/models/albert/configuration_albert.py