Upload optimization.py

optimization.py

@@ -0,0 +1,77 @@
+"""
+"""
+
+from typing import Any
+from typing import Callable
+from typing import ParamSpec
+import spaces
+import torch
+from spaces.zero.torch.aoti import ZeroGPUCompiledModel
+from spaces.zero.torch.aoti import ZeroGPUWeights
+from torch.utils._pytree import tree_map
+
+P = ParamSpec('P')
+
+TRANSFORMER_IMAGE_DIM = torch.export.Dim('image_seq_length', min=4096, max=16384) # min: 0 images, max: 3 (1024x1024) images
+
+TRANSFORMER_DYNAMIC_SHAPES = {
+    'double': {
+        'hidden_states': {
+            1: TRANSFORMER_IMAGE_DIM,
+        },
+        'image_rotary_emb': (
+            {0: TRANSFORMER_IMAGE_DIM + 512},
+            {0: TRANSFORMER_IMAGE_DIM + 512},
+        ),
+    },
+    'single': {
+        'hidden_states': {
+            1: TRANSFORMER_IMAGE_DIM + 512,
+        },
+        'image_rotary_emb': (
+            {0: TRANSFORMER_IMAGE_DIM + 512},
+            {0: TRANSFORMER_IMAGE_DIM + 512},
+        ),
+    },
+}
+
+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):
+
+    blocks = {
+        'double': pipeline.transformer.transformer_blocks,
+        'single': pipeline.transformer.single_transformer_blocks,
+    }
+
+    @spaces.GPU(duration=1200)
+    def compile_block(blocks_kind: str):
+        block = blocks[blocks_kind][0]
+        with spaces.aoti_capture(block) as call:
+            pipeline(*args, **kwargs)
+
+        dynamic_shapes = tree_map(lambda t: None, call.kwargs)
+        dynamic_shapes |= TRANSFORMER_DYNAMIC_SHAPES[blocks_kind]
+
+        with torch.no_grad():      
+            exported = torch.export.export(
+                mod=block,
+                args=call.args,
+                kwargs=call.kwargs,
+                dynamic_shapes=dynamic_shapes,
+            )
+
+        return spaces.aoti_compile(exported, INDUCTOR_CONFIGS).archive_file
+
+    for blocks_kind in ('double', 'single'):
+        archive_file = compile_block(blocks_kind)
+        for block in blocks[blocks_kind]:
+            weights = ZeroGPUWeights(block.state_dict())
+            block.forward = ZeroGPUCompiledModel(archive_file, weights)