update optimization

optimization.py

@@ -0,0 +1,71 @@
+from typing import Any
+from typing import Callable
+from typing import ParamSpec
+import spaces
+import torch
+from torch.utils._pytree import tree_map
+from spaces.zero.torch.aoti import ZeroGPUCompiledModel, ZeroGPUWeights
+
+P = ParamSpec('P')
+
+
+TRANSFORMER_IMAGE_SEQ_LENGTH_DIM = torch.export.Dim('image_seq_length')
+TRANSFORMER_TEXT_SEQ_LENGTH_DIM = torch.export.Dim('text_seq_length')
+
+TRANSFORMER_DYNAMIC_SHAPES = {
+    'hidden_states': {
+        1: TRANSFORMER_IMAGE_SEQ_LENGTH_DIM,
+    },
+    'encoder_hidden_states': {
+        1: TRANSFORMER_TEXT_SEQ_LENGTH_DIM,
+    },
+    'encoder_hidden_states_mask': {
+        1: TRANSFORMER_TEXT_SEQ_LENGTH_DIM,
+    },
+    'image_rotary_emb': ({
+        0: TRANSFORMER_IMAGE_SEQ_LENGTH_DIM,
+    }, {
+        0: TRANSFORMER_TEXT_SEQ_LENGTH_DIM,
+    }),
+}
+
+
+INDUCTOR_CONFIGS = {
+    'conv_1x1_as_mm': True,
+    'epilogue_fusion': False,
+    'coordinate_descent_tuning': True,
+    'coordinate_descent_check_all_directions': True,
+    'max_autotune': True,
+    'triton.cudagraphs': True,
+}
+
+
+def optimize_pipeline_(pipeline: Callable[P, Any], *args: P.args, **kwargs: P.kwargs):
+
+    @spaces.GPU(duration=1500)
+    def compile_transformer():
+        
+        # Only capture what the first `transformer_block` sees.
+        with spaces.aoti_capture(pipeline.transformer.transformer_blocks[0]) as call:
+            pipeline(*args, **kwargs)
+
+        dynamic_shapes = tree_map(lambda t: None, call.kwargs)
+        dynamic_shapes |= TRANSFORMER_DYNAMIC_SHAPES
+
+        # Optionally quantize it.
+        # quantize_(pipeline.transformer, Float8DynamicActivationFloat8WeightConfig())
+        
+        # Only export the first transformer block.
+        exported = torch.export.export(
+            mod=pipeline.transformer.transformer_blocks[0],
+            args=call.args,
+            kwargs=call.kwargs,
+            dynamic_shapes=dynamic_shapes,
+        )
+        return spaces.aoti_compile(exported, INDUCTOR_CONFIGS)
+
+    compiled = compile_transformer()
+    for block in pipeline.transformer.transformer_blocks:
+        weights = ZeroGPUWeights(block.state_dict())
+        compiled_block = ZeroGPUCompiledModel(compiled.archive_file, weights)
+        block.forward = compiled_block