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Update remat rules #2217

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Merged
merged 1 commit into from
Aug 29, 2025
Merged

Update remat rules #2217

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2 changes: 1 addition & 1 deletion MaxText/configs/base.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -241,7 +241,7 @@ set_remat_policy_on_pipeline_iterations: True
set_remat_policy_on_layers_per_stage: False


# Choose 'remat_policy' between 'minimal', 'save_dot_with_context_except_mlp', 'save_dot_except_mlpwi', 'save_dot_except_mlp',
# Choose 'remat_policy' between 'minimal_with_context', 'minimal', 'save_dot_with_context_except_mlp', 'save_dot_except_mlpwi', 'save_dot_except_mlp',
# 'save_qkv_proj', 'qkv_proj_offloaded', 'custom', 'minimal_offloaded', 'save_out_proj' and 'full'.
# These options offer a trade-off between speed (fastest to slowest) and HBM usage (highest to lowest)
remat_policy: 'full'
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2 changes: 1 addition & 1 deletion MaxText/configs/models/gpu/llama2_7b.yml
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Expand Up @@ -8,7 +8,7 @@ max_target_length: 4096
model_name: "llama2-7b"
enable_checkpointing: False
attention: "cudnn_flash_te"
remat_policy: "minimal_flash"
remat_policy: "minimal_with_context"
use_iota_embed: True
scan_layers: False
dataset_type: "synthetic"
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2 changes: 1 addition & 1 deletion MaxText/configs/models/gpu/llama3_8b.yml
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Expand Up @@ -23,7 +23,7 @@ steps: 30
per_device_batch_size: 12
max_target_length: 8192
attention: "cudnn_flash_te"
remat_policy: "minimal_flash"
remat_policy: "minimal_with_context"
use_iota_embed: True
dataset_type: "synthetic"
reuse_example_batch: 1
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2 changes: 1 addition & 1 deletion MaxText/configs/models/gpu/mixtral_8x7b.yml
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Expand Up @@ -23,7 +23,7 @@ steps: 30
per_device_batch_size: 12
max_target_length: 4096
attention: "cudnn_flash_te"
remat_policy: "minimal_flash"
remat_policy: "minimal_with_context"
use_iota_embed: True
dataset_type: "synthetic"
reuse_example_batch: 1
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54 changes: 41 additions & 13 deletions MaxText/layers/decoders.py
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Expand Up @@ -259,13 +259,34 @@ def setup(self):
config=self.config, mesh=self.mesh, layers=pipeline_stage_module, remat_policy=remat_policy
)

def minimal_policy(self, with_context=False):
"""Helper for creating minimal checkpoint policies."""
names = [
"query_proj",
"value_proj",
"key_proj",
"qkv_proj",
"out_proj",
"mlpwi_0",
"mlpwi_1",
"mlpwi",
"mlpwo",
]
if with_context:
names.append("context")
return jax.checkpoint_policies.save_only_these_names(*names)

def get_remat_policy(self):
"""Get remat policy"""
policy = None
cfg = self.config
if cfg.remat_policy != "none":
if cfg.remat_policy == "minimal":
policy = jax.checkpoint_policies.checkpoint_dots_with_no_batch_dims
if cfg.remat_policy == "minimal_with_context":
# save all
policy = self.minimal_policy(with_context=True)
elif cfg.remat_policy == "minimal":
# save all except context
policy = self.minimal_policy()
elif cfg.remat_policy == "save_dot_with_context_except_mlp":
policy = jax.checkpoint_policies.save_only_these_names(
"query_proj",
Expand Down Expand Up @@ -307,21 +328,30 @@ def get_remat_policy(self):
offload_dst="pinned_host",
)
elif cfg.remat_policy == "minimal_offloaded":
policy = jax.checkpoint_policies.offload_dot_with_no_batch_dims(offload_src="device", offload_dst="pinned_host")
# offload all except context
policy = jax.checkpoint_policies.save_and_offload_only_these_names(
names_which_can_be_saved=[],
names_which_can_be_offloaded=[
"query_proj",
"value_proj",
"key_proj",
"qkv_proj",
"out_proj",
"mlpwi_0",
"mlpwi_1",
"mlpwi",
"mlpwo",
],
offload_src="device",
offload_dst="pinned_host",
)
elif cfg.remat_policy == "custom":
policy = jax.checkpoint_policies.save_and_offload_only_these_names(
names_which_can_be_saved=cfg.tensors_on_device,
names_which_can_be_offloaded=cfg.tensors_to_offload,
offload_src="device",
offload_dst="pinned_host",
)
elif cfg.remat_policy == "minimal_flash":
policy = jax.checkpoint_policies.save_from_both_policies(
jax.checkpoint_policies.checkpoint_dots_with_no_batch_dims,
jax.checkpoint_policies.save_only_these_names(
"context",
),
)
elif cfg.remat_policy == "save_out_proj":
policy = jax.checkpoint_policies.save_only_these_names(
"out_proj",
Expand Down Expand Up @@ -742,9 +772,7 @@ def __call__(
# Iterate over the two layer groups (dense and MoE) and apply layer transformation
for layer, num_layers, layer_prefix in zip(layers, num_layers_list, layer_prefixes):
for index in range(num_layers):
y = layer(
config=cfg, mesh=mesh, name=f"{layer_prefix}_{index}", quant=self.quant, model_mode=self.model_mode
)(
y = layer(config=cfg, mesh=mesh, name=f"{layer_prefix}_{index}", quant=self.quant, model_mode=self.model_mode)(
y,
decoder_segment_ids,
decoder_positions,
Expand Down
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