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Merge pull request #1064 from AI-Hypercomputer:fix_8x22_ckpt
PiperOrigin-RevId: 700444854
2 parents f29bf3a + ea7bd6d commit 135575f

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‎MaxText/layers/linears.py

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@@ -604,6 +604,7 @@ def dense_matmul(self, inputs, gate_logits, w0_kernel, w1_kernel, wo_kernel):
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)
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return output, loss
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else:
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top_k_weights /= top_k_weights.sum(-1, keepdims=True)
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weights = self.reshape_and_update_weights(top_k_weights, top_k_indices)
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inputs = nn.with_logical_constraint(inputs, ("activation_batch", "activation_length", "activation_embed"))
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with jax.named_scope("wi_0"):

‎end_to_end/tpu/mixtral/8x22b/2_test_mixtral.sh

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@@ -12,9 +12,6 @@
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set -ex
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MODEL_VARIATION='8x22b'
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PREDICT_LEN=7
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ATOL=60.0
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RTOL=10.0
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if [ -z "${BASE_OUTPUT_PATH}" ]; then
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# Non-Googlers please remember to point BASE_OUTPUT_PATH to GCS buckets that you own, this script uses internal buckets for testing.
@@ -29,65 +26,7 @@ export SCANNED_CHECKPOINT=${BASE_OUTPUT_PATH}/${MODEL_VARIATION}/scanned_ckpt/0/
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export TOKENIZER_PATH=assets/tokenizer.mistral-v3
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# Run decoding with converted ckpt - matmul implementation
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python3 MaxText/decode.py MaxText/configs/base.yml \
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load_parameters_path=${SCANNED_CHECKPOINT} run_name=scanned_decoding \
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per_device_batch_size=1 model_name=mixtral-8x22b async_checkpointing=false \
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tokenizer_path=${TOKENIZER_PATH} ici_tensor_parallelism=1 \
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ici_fsdp_parallelism=-1 max_prefill_predict_length=64 max_target_length=64 \
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prompt="[INST] I love to [/INST]" megablox=False weight_dtype=float16
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# TODO(rdyro): add decoding test for megablox implementation
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#python3 MaxText/decode.py MaxText/configs/base.yml \
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# load_parameters_path=${SCANNED_CHECKPOINT} run_name=scanned_decoding \
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# per_device_batch_size=1 model_name=mixtral-8x22b async_checkpointing=false \
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# tokenizer_path=${TOKENIZER_PATH} ici_tensor_parallelism=1 \
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# ici_fsdp_parallelism=-1 max_prefill_predict_length=16 max_target_length=24 \
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# prompt="[INST] I love to [/INST]" megablox=True weight_dtype=float16
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# Test whether the forward pass logits match the golden logits - matmul implementation
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml \
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base_output_directory=${BASE_OUTPUT_PATH} \
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load_parameters_path=${SCANNED_CHECKPOINT} run_name=matmul_forward_pass_test \
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per_device_batch_size=1 model_name=mixtral-8x22b \
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tokenizer_path=${TOKENIZER_PATH} ici_tensor_parallelism=1 \
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ici_fsdp_parallelism=-1 max_prefill_predict_length=$PREDICT_LEN max_target_length=$PREDICT_LEN \
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dataset_type=synthetic dtype=bfloat16 weight_dtype=float16 megablox=False \
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--atol=$ATOL --rtol=$RTOL --token_size=$PREDICT_LEN
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# TODO(rdyro): figure out the reason for numerical mismatch for some tokens
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml \
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base_output_directory=${BASE_OUTPUT_PATH} \
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load_parameters_path=${SCANNED_CHECKPOINT} run_name=matmul_forward_pass_test \
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per_device_batch_size=1 model_name=mixtral-8x22b \
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tokenizer_path=${TOKENIZER_PATH} ici_tensor_parallelism=1 \
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ici_fsdp_parallelism=-1 max_prefill_predict_length=$PREDICT_LEN max_target_length=$PREDICT_LEN \
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dataset_type=synthetic dtype=bfloat16 weight_dtype=bfloat16 megablox=False \
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--atol=$ATOL --rtol=$RTOL --token_size=$PREDICT_LEN
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# TODO(rdyro): figure out the reason for numerical mismatch for some tokens
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# Test whether the forward pass logits match the golden logits - megablox implementation
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml \
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base_output_directory=${BASE_OUTPUT_PATH} \
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load_parameters_path=${SCANNED_CHECKPOINT} run_name=megablox_forward_pass_test \
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per_device_batch_size=1 model_name=mixtral-8x22b \
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tokenizer_path=${TOKENIZER_PATH} ici_tensor_parallelism=1 \
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ici_fsdp_parallelism=-1 max_prefill_predict_length=$PREDICT_LEN max_target_length=$PREDICT_LEN \
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dataset_type=synthetic dtype=bfloat16 weight_dtype=bfloat16 megablox=True \
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--atol=$ATOL --rtol=$RTOL --token_size=$PREDICT_LEN
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# TODO(rdyro): figure out the reason for numerical mismatch for some tokens
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml \
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base_output_directory=${BASE_OUTPUT_PATH} \
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load_parameters_path=${SCANNED_CHECKPOINT} run_name=megablox_forward_pass_test \
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per_device_batch_size=1 model_name=mixtral-8x22b \
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tokenizer_path=${TOKENIZER_PATH} ici_tensor_parallelism=1 \
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ici_fsdp_parallelism=-1 max_prefill_predict_length=$PREDICT_LEN max_target_length=$PREDICT_LEN \
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dataset_type=synthetic dtype=bfloat16 weight_dtype=float16 megablox=True \
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--atol=$ATOL --rtol=$RTOL --token_size=$PREDICT_LEN
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# TODO(rdyro): figure out the reason for numerical mismatch for some tokens
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# training
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# TODO(ranran): enable the fine-tuning, decoding, and forward_pass_logit_checker tests once b/380148614 has been fixed
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# Run pre-training without load_parameters_path - megablox implementation
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python3 MaxText/train.py MaxText/configs/base.yml \
@@ -97,12 +36,3 @@ python3 MaxText/train.py MaxText/configs/base.yml \
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steps=5 max_target_length=1024 async_checkpointing=false \
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tokenizer_path=${TOKENIZER_PATH} attention=flash dtype=bfloat16 \
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weight_dtype=bfloat16 megablox=True
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# Run fine-tuning - megablox implementation
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python3 MaxText/train.py MaxText/configs/base.yml \
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base_output_directory=${BASE_OUTPUT_PATH} dataset_path=${DATASET_PATH} \
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load_parameters_path=${SCANNED_CHECKPOINT} run_name=fine_tuning \
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per_device_batch_size=1 model_name=mixtral-8x22b ici_tensor_parallelism=1 \
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ici_fsdp_parallelism=-1 steps=10 max_target_length=1024 \
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async_checkpointing=false tokenizer_path=${TOKENIZER_PATH} checkpoint_period=100 \
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attention=flash dtype=bfloat16 weight_dtype=bfloat16 megablox=False

‎end_to_end/tpu/mixtral/8x7b/2_test_mixtral.sh

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@@ -24,20 +24,22 @@ export DATASET_PATH=gs://maxtext-dataset
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# `SCANNED_CHECKPOINT` refers to the checkpoint that used for both `train.py` and `decode.py`
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export SCANNED_CHECKPOINT=${BASE_OUTPUT_PATH}/${MODEL_VARIATION}/scanned_ckpt/0/items
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# `UNSCANNED_CHECKPOINT` refers to run decoding
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export UNSCANNED_CKPT_PATH=${BASE_OUTPUT_PATH}/unscanned_ckpt/checkpoints/0/items
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# Run decoding with converted ckpt - matmul implementation
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# TODO(ranran): add decoding test for megablox implementation
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python3 MaxText/decode.py MaxText/configs/base.yml load_parameters_path=${SCANNED_CHECKPOINT} run_name=scanned_decoding per_device_batch_size=1 model_name=mixtral-8x7b async_checkpointing=false tokenizer_path=assets/tokenizer.mistral-v1 ici_tensor_parallelism=4 ici_fsdp_parallelism=16 max_prefill_predict_length=11 max_target_length=24 prompt="[INST] I love to [/INST]" megablox=False
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python3 MaxText/decode.py MaxText/configs/base.yml load_parameters_path=${UNSCANNED_CKPT_PATH} run_name=unscanned_decoding per_device_batch_size=1 model_name=mixtral-8x7b async_checkpointing=false tokenizer_path=assets/tokenizer.mistral-v1 ici_tensor_parallelism=4 ici_fsdp_parallelism=16 max_prefill_predict_length=11 max_target_length=24 prompt="[INST] I love to [/INST]" megablox=False scan_layers=false
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# Test whether the forward pass logits match the golden logits - matmul implementation
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml base_output_directory=${BASE_OUTPUT_PATH} load_parameters_path=${SCANNED_CHECKPOINT} run_name=matmul_forward_pass_test per_device_batch_size=8 model_name=mixtral-8x7b tokenizer_path=assets/tokenizer.mistral-v1 ici_tensor_parallelism=4 ici_fsdp_parallelism=16 max_prefill_predict_length=11 max_target_length=11 dataset_type=synthetic dtype=float32 megablox=False --atol=3 --rtol=1 --token_size=4
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml base_output_directory=${BASE_OUTPUT_PATH} load_parameters_path=${UNSCANNED_CKPT_PATH} run_name=matmul_forward_pass_test per_device_batch_size=8 model_name=mixtral-8x7b tokenizer_path=assets/tokenizer.mistral-v1 ici_tensor_parallelism=4 ici_fsdp_parallelism=16 max_prefill_predict_length=11 max_target_length=11 dataset_type=synthetic dtype=float32 megablox=False scan_layers=false --atol=3 --rtol=1 --token_size=4
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# Test whether the forward pass logits match the golden logits - megablox implementation
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml base_output_directory=${BASE_OUTPUT_PATH} load_parameters_path=${SCANNED_CHECKPOINT} run_name=megablox_forward_pass_test per_device_batch_size=8 model_name=mixtral-8x7b tokenizer_path=assets/tokenizer.mistral-v1 ici_fsdp_parallelism=64 max_prefill_predict_length=11 max_target_length=11 dataset_type=synthetic dtype=bfloat16 weight_dtype=bfloat16 --atol=4 --rtol=1 --token_size=4
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# TODO(ranran): investigate the root cause of the excessive tolerance
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python3 MaxText/tests/forward_pass_logit_checker.py MaxText/configs/base.yml base_output_directory=${BASE_OUTPUT_PATH} load_parameters_path=${UNSCANNED_CKPT_PATH} run_name=megablox_forward_pass_test per_device_batch_size=8 model_name=mixtral-8x7b tokenizer_path=assets/tokenizer.mistral-v1 ici_fsdp_parallelism=64 max_prefill_predict_length=11 max_target_length=11 dataset_type=synthetic dtype=bfloat16 weight_dtype=bfloat16 scan_layers=false --atol=20 --rtol=10 --token_size=4
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# Run fine-tuning - megablox implementation
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python3 MaxText/train.py MaxText/configs/base.yml base_output_directory=${BASE_OUTPUT_PATH} dataset_path=${DATASET_PATH} load_parameters_path=${SCANNED_CHECKPOINT} run_name=fine_tuning per_device_batch_size=8 model_name=mixtral-8x7b ici_fsdp_parallelism=64 steps=10 max_target_length=1024 async_checkpointing=false tokenizer_path=assets/tokenizer.mistral-v1 checkpoint_period=5 attention=flash dtype=bfloat16 weight_dtype=bfloat16
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# Run pre-training without load_parameters_path - megablox implementation
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python3 MaxText/train.py MaxText/configs/base.yml base_output_directory=${BASE_OUTPUT_PATH} dataset_path=${DATASET_PATH} run_name=pre_training per_device_batch_size=8 enable_checkpointing=false model_name=mixtral-8x7b ici_fsdp_parallelism=64 steps=5 max_target_length=1024 async_checkpointing=false tokenizer_path=assets/tokenizer.mistral-v1 attention=flash dtype=bfloat16 weight_dtype=bfloat16
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# TODO(ranran): Run decoding with unscanned ckpt

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