# Copyright 2022 Cerebras Systems.
#
# 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.
[docs]def set_defaults(params):
    """
    Update any missing parameters in the params dictionary with default values
    Args:
        params: The dictionary containing the params
    """
    if params["train_input"]["data_processor"] == "Gpt2SyntheticDataProcessor":
        if "train_input" in params:
            params["train_input"]["vocab_size"] = params["train_input"].get(
                "vocab_size", params["model"]["vocab_size"]
            )
            assert (
                params["train_input"]["vocab_size"]
                == params["model"]["vocab_size"]
            ), f"Found different vocab_size in train_input ({params['train_input']['vocab_size']}) vs. model ({params['model']['vocab_size']})"
            params["train_input"]["max_sequence_length"] = params[
                "train_input"
            ].get(
                "max_sequence_length",
                params["model"]["max_position_embeddings"],
            )
        if "eval_input" in params:
            params["eval_input"]["vocab_size"] = params["eval_input"].get(
                "vocab_size", params["model"]["vocab_size"]
            )
            assert (
                params["eval_input"]["vocab_size"]
                == params["model"]["vocab_size"]
            ), f"Found different vocab_size in eval_input ({params['eval_input']['vocab_size']}) vs. model ({params['model']['vocab_size']})"
            params["eval_input"]["max_sequence_length"] = params[
                "eval_input"
            ].get(
                "max_sequence_length",
                params["model"]["max_position_embeddings"],
            )
    params["model"]["fp16_type"] = params["model"].get("fp16_type", "bfloat16")
    params["optimizer"]["loss_scaling_factor"] = params["optimizer"].get(
        "loss_scaling_factor", 1.0
    )
    params["optimizer"]["log_summaries"] = params["optimizer"].get(
        "log_summaries", False
    )
    params["runconfig"]["precision_opt_level"] = params["runconfig"].get(
        "precision_opt_level", 1
    )
    from modelzoo.transformers.pytorch.gpt2.utils import set_attention_params
    set_attention_params(params)