sample generation runs

generate_samples_gpt2.py

+# coding=utf-8
+# Copyright (c) 2019, NVIDIA CORPORATION.  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.
+
+"""Sample Generate GPT2"""
+
+from megatron import get_args
+from megatron import get_tokenizer
+from megatron import print_rank_0
+from megatron.checkpointing import load_checkpoint
+from megatron.initialize import initialize_megatron
+from megatron.model import GPT2Model
+from megatron.training import get_model
+from megatron.text_generation_utils import generate_and_write_samples_unconditional
+from megatron.text_generation_utils import generate_samples_input_from_file
+from megatron.text_generation_utils import generate_samples_interactive
+
+
+def model_provider():
+    """Build the model."""
+
+    print_rank_0('building GPT2 model ...')
+    model = GPT2Model(num_tokentypes=0, parallel_output=False)
+
+    return model
+
+
+def add_text_generate_args(parser):
+    """Text generation arguments."""
+    group = parser.add_argument_group(title='text generation')
+
+    group.add_argument("--temperature", type=float, default=1.0,
+                       help='Sampling temperature.')
+    group.add_argument("--greedy", action='store_true', default=False,
+                       help='Use greedy sampling.')
+    group.add_argument("--top_p", type=float, default=0.0,
+                       help='Top p sampling.')
+    group.add_argument("--top_k", type=int, default=0,
+                       help='Top k sampling.')
+    group.add_argument("--out-seq-length", type=int, default=1024,
+                       help='Size of the output generated text.')
+    group.add_argument("--sample-input-file", type=str, default=None,
+                       help='Get input from file instead of interactive mode, '
+                       'each line is an input.')
+    group.add_argument("--sample-output-file", type=str, default=None,
+                       help='Output file got from --sample-input-file')
+    group.add_argument("--num-samples", type=int, default=0,
+                       help='Number of samples to generate unconditionally, '
+                       'defaults to 0 and interactive conditional sampling')
+    group.add_argument("--genfile", type=str,
+                       help='Output file when generating unconditionally')
+    group.add_argument("--recompute", action='store_true',
+                       help='During generation recompute all attention '
+                       'instead of using previously computed keys/values.')
+
+    return parser
+
+
+def main():
+    """Main program."""
+
+    initialize_megatron(extra_args_provider=add_text_generate_args,
+                        args_defaults={'tokenizer_type': 'GPT2BPETokenizer'})
+
+    # Set up model and load checkpoint.
+    model = get_model(model_provider)
+    args = get_args()
+    if args.load is not None:
+        _ = load_checkpoint(model, None, None)
+
+    # Generate samples.
+    if args.num_samples == 0:
+        args.batch_size = 1
+        if args.sample_input_file != "":
+            generate_samples_input_from_file(model)
+        else:
+            generate_samples_interactive(model)
+    else:
+        generate_and_write_samples_unconditional(model)
+
+
+if __name__ == "__main__":
+
+    main()

generate_samples.py → megatron/text_generation_utils.py

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""Sample Generate GPT2"""
+"""Utilities for generating text."""
 
 import copy
 import json
@@ -26,23 +26,9 @@ import torch.nn.functional as F
 from megatron import get_args
 from megatron import get_tokenizer
 from megatron import mpu
-from megatron import print_rank_0
-from megatron.checkpointing import load_checkpoint
-from megatron.initialize import initialize_megatron
-from megatron.model import GPT2Model
-from megatron.training import get_model
 from megatron.utils import get_ltor_masks_and_position_ids
 
 
-def model_provider():
-    """Build the model."""
-
-    print_rank_0('building GPT2 model ...')
-    model = GPT2Model(num_tokentypes=0, parallel_output=False)
-
-    return model
-
-
 def get_batch(context_tokens):
     """Generate batch from context tokens."""
     args = get_args()
@@ -280,7 +266,7 @@ def generate_samples_unconditional(model):
             break
 
 
-def write_and_generate_samples_unconditional(model):
+def generate_and_write_samples_unconditional(model):
 
     args = get_args()
     assert args.genfile is not None
@@ -423,61 +409,3 @@ def sample_sequence_batch(model, context_tokens, context_lengths,
             yield tokens, lengths
             if done:
                 break
-
-def add_text_generate_args(parser):
-    """Text generation arguments."""
-    group = parser.add_argument_group(title='text generation')
-
-    group.add_argument("--temperature", type=float, default=1.0,
-                       help='Sampling temperature.')
-    group.add_argument("--greedy", action='store_true', default=False,
-                       help='Use greedy sampling.')
-    group.add_argument("--top_p", type=float, default=0.0,
-                       help='Top p sampling.')
-    group.add_argument("--top_k", type=int, default=0,
-                       help='Top k sampling.')
-    group.add_argument("--out-seq-length", type=int, default=1024,
-                       help='Size of the output generated text.')
-    group.add_argument("--sample-input-file", type=str, default=None,
-                       help='Get input from file instead of interactive mode, '
-                       'each line is an input.')
-    group.add_argument("--sample-output-file", type=str, default=None,
-                       help='Output file got from --sample-input-file')
-    group.add_argument("--num-samples", type=int, default=0,
-                       help='Number of samples to generate unconditionally, '
-                       'defaults to 0 and interactive conditional sampling')
-    group.add_argument("--genfile", type=str,
-                       help='Output file when generating unconditionally')
-    group.add_argument("--recompute", action='store_true',
-                       help='During generation recompute all attention '
-                       'instead of using previously computed keys/values.')
-
-    return parser
-
-
-def main():
-    """Main program."""
-
-    initialize_megatron(extra_args_provider=add_text_generate_args,
-                        args_defaults={'tokenizer_type': 'GPT2BPETokenizer'})
-
-    # Set up model and load checkpoint.
-    model = get_model(model_provider)
-    args = get_args()
-    if args.load is not None:
-        _ = load_checkpoint(model, None, None)
-
-    # Generate samples.
-    if args.num_samples == 0:
-        args.batch_size = 1
-        if args.sample_input_file != "":
-            generate_samples_input_from_file(model)
-        else:
-            generate_samples_interactive(model)
-    else:
-        write_and_generate_samples_unconditional(model)
-
-
-if __name__ == "__main__":
-
-    main()