Fix for TransformerLayer MLP parameters not being set with specific hyperparameters

[OlegSudakov]

What does this PR do ?

Detailed description here: #8846
This PR fixes Transformer layer MLP hyperparameters not being set with model.mcore_gpt=False, model.transformer_engine=True, and model.megatron_amp_O2=True.

Collection: NLP

Changelog

• Passing missing arguments to layer constructors.

Usage

• Add the following lines to opt/NeMo/examples/nlp/language_modeling/megatron_gpt_pretraining.py after model initialization to debug:

logging.warning(f"DEBUG: layernorm_mlp.activation={model.model.module.language_model.encoder.layers._modules['0'].layernorm_mlp.activation}")
logging.warning(f"DEBUG: layernorm_mlp.use_bias={model.model.module.language_model.encoder.layers._modules['0'].layernorm_mlp.use_bias}")
logging.warning(f"DEBUG: layernorm_mlp.normalization={model.model.module.language_model.encoder.layers._modules['0'].layernorm_mlp.normalization}")
logging.warning(f"DEBUG: layernorm_mlp.layernorm_mlp.fc1_weight.shape={model.model.module.language_model.encoder.layers._modules['0'].layernorm_mlp.fc1_weight.shape}")
logging.warning(f"DEBUG: layernorm_mlp.layernorm_mlp.fc2_weight.shape={model.model.module.language_model.encoder.layers._modules['0'].layernorm_mlp.fc2_weight.shape}")

Test with the following script with and without the changes:

#!/bin/bash

python /opt/NeMo/examples/nlp/language_modeling/megatron_gpt_pretraining.py \
    model.mcore_gpt=False \
    model.transformer_engine=True \
    trainer.precision=bf16 \
    model.megatron_amp_O2=True \
    model.activation=fast-swiglu \
    model.bias=false \
    model.normalization=rmsnorm \

The bias, normalization, and activation should be correctly set with the fix.

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