Add test for text-generation pipeline (#1139)

* Add test for text-generation pipeline

* Fix test

* Update test_text_generation.py

* Remove model_stub fixture

* local model stub

* Add HF comparison

* Move imports

tests/deepsparse/transformers/pipelines/test_text_generation.py

@@ -0,0 +1,44 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+import pytest
+from deepsparse import Pipeline
+
+
+@pytest.mark.slow
+def test_codegen():
+    model_stub = (
+        "zoo:nlg/text_generation/codegen_mono-350m/pytorch/"
+        "huggingface/bigpython_bigquery_thepile/base-none"
+    )
+    pipeline = Pipeline.create(
+        task="text_generation",
+        model_path=model_stub,
+        max_generated_tokens=16,
+        prompt_processing_sequence_length=1,
+        use_deepsparse_cache=False,
+    )
+    prompt = "def fib():"
+    out = pipeline(sequences=prompt)
+    nm_output = prompt + out.sequences[0]
+
+    tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-mono")
+    model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-mono")
+    input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+    generated_ids = model.generate(input_ids, max_new_tokens=16)
+    hf_output = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
+
+    assert nm_output == hf_output