Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add profiler annotation for the decoderonly example #8034

Closed
wants to merge 1 commit into from
Closed
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions examples/decoder_only_model.py
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
import torch.nn.functional as F
from torch import nn

import torch_xla.debug.profiler as xp

# the default config is intentionally kept low to make it runable on a sigle tpu v2-8 core.
@dataclass
Expand Down Expand Up @@ -44,6 +45,7 @@ def __init__(self, hidden_size, eps=1e-6):
self.weight = nn.Parameter(torch.ones(hidden_size))
self.variance_epsilon = eps

@xp.trace_me("RMSNorm")
def forward(self, hidden_states):
input_dtype = hidden_states.dtype
hidden_states = hidden_states.to(torch.float32)
Expand Down Expand Up @@ -79,6 +81,7 @@ def __init__(self, config: DecoderOnlyConfig):
self.num_heads * self.head_dim, self.hidden_size, bias=False)
self.flash_attention_impl = None

@xp.trace_me("attention")
def forward(
self,
hidden_states: torch.Tensor,
Expand Down Expand Up @@ -153,6 +156,7 @@ def __init__(self, config: DecoderOnlyConfig):
self.intermediate_size, self.hidden_size, bias=False)
self.act_fn = F.silu

@xp.trace_me("MLP")
def forward(self, x):
# [B, S, H] -> [B, S, I]
up_proj = self.up_proj(x)
Expand All @@ -173,6 +177,7 @@ def __init__(self, config: DecoderOnlyConfig):
self.input_layernorm = RMSNorm(config.hidden_size)
self.post_attention_layernorm = RMSNorm(config.hidden_size)

@xp.trace_me("DecoderLayer")
def forward(
self,
hidden_states: torch.Tensor,
Expand Down Expand Up @@ -209,6 +214,7 @@ def __init__(self, config: DecoderOnlyConfig):
self.norm = RMSNorm(config.hidden_size)
self.output = nn.Linear(config.hidden_size, self.vocab_size, bias=False)

@xp.trace_me("DecoderOnlyModel")
def forward(
self,
input_ids: torch.LongTensor = None,
Expand Down
Loading