More formatting (mlc-ai#1099)

Author: junrushao

tests/debug/compare_lib.py renamed to tests/python/legacy/compare_lib.py

@@ -1,17 +1,14 @@
-from typing import List
-
 import argparse
-import os
 import json
+import os
+from typing import List
 
-import tvm
-from tvm import relax
-from tvm import rpc
-from tvm.relax.testing.lib_comparator import LibCompareVMInstrument
 import numpy as np
-
 import torch
+import tvm
 from transformers import AutoTokenizer, LlamaTokenizer
+from tvm import relax, rpc
+from tvm.relax.testing.lib_comparator import LibCompareVMInstrument
 
 from mlc_llm import utils
 
@@ -53,7 +50,7 @@ def compare(
 
         if self.time_eval and name not in self.time_eval_results:
             res = self.mod.time_evaluator(
-                name, self.device, number=20, repeat=3#, cache_flush_bytes=256 * 10**6
+                name, self.device, number=20, repeat=3  # , cache_flush_bytes=256 * 10**6
             )(*new_args)
             self.time_eval_results[name] = (res.mean, 1)
             print(f"Time-eval result {name} on {self.device}: {res}")
@@ -121,9 +118,7 @@ def __init__(self, args):
                 )
             )
             self.cmp_device = tvm.device(args.cmp_device)
-        self.const_params_dict = utils.load_params(
-            args.artifact_path, self.primary_device
-        )
+        self.const_params_dict = utils.load_params(args.artifact_path, self.primary_device)
         self.cmp_instrument = LibCompare(
             self.lib,
             self.cmp_device,
@@ -134,9 +129,7 @@ def __init__(self, args):
 
 
 def deploy_to_pipeline(args) -> None:
-    with open(
-        os.path.join(args.artifact_path, "params", "mlc-chat-config.json"), "r"
-    ) as f:
+    with open(os.path.join(args.artifact_path, "params", "mlc-chat-config.json"), "r") as f:
         config = json.load(f)
 
     primary_device = tvm.device(args.primary_device)
@@ -157,18 +150,14 @@ def deploy_to_pipeline(args) -> None:
         tokenizer(args.prompt, return_tensors="pt").input_ids.to(torch.int32).numpy(),
         primary_device,
     )
-    first_sampled_token = tvm.nd.array(
-        np.array([[6234]]).astype("int32"), primary_device
-    )
+    first_sampled_token = tvm.nd.array(np.array([[6234]]).astype("int32"), primary_device)
     seq_len_shape = tvm.runtime.ShapeTuple([inputs.shape[1]])
     second_seq_len_shape = tvm.runtime.ShapeTuple([inputs.shape[1] + 1])
     kv_caches = state.vm["create_kv_cache"]()
 
     print("Running inference...")
     print("======================= Starts Encoding =======================")
-    logits, kv_caches = state.vm["prefill"](
-        inputs, seq_len_shape, kv_caches, const_params
-    )
+    logits, kv_caches = state.vm["prefill"](inputs, seq_len_shape, kv_caches, const_params)
     print_as_table(
         sorted(
             state.cmp_instrument.time_eval_results.items(),

tests/debug/dump_intermediate.py renamed to tests/python/legacy/dump_intermediate.py

@@ -1,12 +1,12 @@
 import argparse
 import os
+import pickle
 
 import numpy as np
 import torch
 import tvm
 from transformers import AutoTokenizer
 from tvm import relax
-import pickle
 
 from mlc_llm import utils
 
@@ -77,12 +77,8 @@ def deploy_to_pipeline(args) -> None:
     )
 
     print("Tokenizing...")
-    inputs = (
-        tokenizer(args.prompt, return_tensors="pt").input_ids.to(torch.int32).numpy()
-    )
-    first_sampled_token = tvm.nd.array(
-        np.array([[6234]]).astype("int32"), primary_device
-    )
+    inputs = tokenizer(args.prompt, return_tensors="pt").input_ids.to(torch.int32).numpy()
+    first_sampled_token = tvm.nd.array(np.array([[6234]]).astype("int32"), primary_device)
     seq_len_shape = tvm.runtime.ShapeTuple([inputs.shape[1]])
     second_seq_len_shape = tvm.runtime.ShapeTuple([inputs.shape[1] + 1])
     kv_caches = state.vm["create_kv_cache"]()

tests/evaluate.py renamed to tests/python/legacy/evaluate.py

@@ -58,9 +58,7 @@ def compare(
                 repeat=3,
             )(*new_args).mean
             shapes = [arg.shape for arg in new_args]
-            total_bytes = sum(
-                arg.numpy().size * arg.numpy().itemsize for arg in new_args
-            )
+            total_bytes = sum(arg.numpy().size * arg.numpy().itemsize for arg in new_args)
             self.time_eval_results[name] = (res, 1, shapes, total_bytes)
         else:
             record = self.time_eval_results[name]
@@ -177,9 +175,7 @@ def deploy_to_pipeline(args) -> None:  # pylint: disable=too-many-locals
         print("Profiling...")
         kv_caches = vm["create_kv_cache"]()
 
-        logits, kv_caches = vm["prefill"](
-            inputs, seq_len_shape, kv_caches, const_params
-        )
+        logits, kv_caches = vm["prefill"](inputs, seq_len_shape, kv_caches, const_params)
         print("======================= Encoding Profiling =======================")
         print_as_table(
             sorted(

tests/debug/test_batching_llama.py renamed to tests/python/legacy/test_batching_llama.py

@@ -3,11 +3,12 @@
 import dataclasses
 import unittest
 
-from mlc_llm import BuildArgs, utils, core
+from mlc_llm import BuildArgs, core, utils
+
 
 def old_make_args():
     """The exact old way of creating `ArgumentParser`, used to test whether
-    `BuildArgs` is equivalent to this. """
+    `BuildArgs` is equivalent to this."""
     args = argparse.ArgumentParser()
     args.add_argument(
         "--model",
@@ -17,7 +18,7 @@ def old_make_args():
             'The name of the model to build. If it is "auto", we will '
             'automatically set the model name according to "--model-path", '
             '"hf-path" or the model folders under "--artifact-path/models"'
-        )
+        ),
     )
     args.add_argument(
         "--hf-path",
@@ -30,19 +31,16 @@ def old_make_args():
         type=str,
         choices=[*utils.quantization_schemes.keys()],
         default=list(utils.quantization_schemes.keys())[0],
-        help="The quantization mode we use to compile."
+        help="The quantization mode we use to compile.",
     )
     args.add_argument(
         "--max-seq-len",
         type=int,
         default=-1,
-        help="The maximum allowed sequence length for the model."
+        help="The maximum allowed sequence length for the model.",
     )
     args.add_argument(
-        "--target",
-        type=str,
-        default="auto",
-        help="The target platform to compile the model for."
+        "--target", type=str, default="auto", help="The target platform to compile the model for."
     )
     args.add_argument(
         "--reuse-lib",
@@ -51,10 +49,7 @@ def old_make_args():
         help="Whether to reuse a previously generated lib.",
     )
     args.add_argument(
-        "--artifact-path",
-        type=str,
-        default="dist",
-        help="Where to store the output."
+        "--artifact-path", type=str, default="dist", help="Where to store the output."
     )
     args.add_argument(
         "--use-cache",
@@ -66,13 +61,13 @@ def old_make_args():
         "--debug-dump",
         action="store_true",
         default=False,
-        help="Whether to dump debugging files during compilation."
+        help="Whether to dump debugging files during compilation.",
     )
     args.add_argument(
         "--debug-load-script",
         action="store_true",
         default=False,
-        help="Whether to load the script for debugging."
+        help="Whether to load the script for debugging.",
     )
     args.add_argument(
         "--llvm-mingw",
@@ -81,10 +76,7 @@ def old_make_args():
         help="/path/to/llvm-mingw-root, use llvm-mingw to cross compile to windows.",
     )
     args.add_argument(
-        "--system-lib",
-        action="store_true",
-        default=False,
-        help="A parameter to `relax.build`."
+        "--system-lib", action="store_true", default=False, help="A parameter to `relax.build`."
     )
     args.add_argument(
         "--sep-embed",
@@ -99,17 +91,20 @@ def old_make_args():
 
     return args
 
+
 # Referred to HfArgumentParserTest from https://github.com/huggingface/
 # transformers/blob/e84bf1f734f87aa2bedc41b9b9933d00fc6add98/tests/utils
 # /test_hf_argparser.py#L143
 class BuildArgsTest(unittest.TestCase):
     """Tests whether BuildArgs reaches parity with regular ArgumentParser."""
-    def argparsers_equal(self, parse_a: argparse.ArgumentParser, 
-                         parse_b: argparse.ArgumentParser):
+
+    def argparsers_equal(self, parse_a: argparse.ArgumentParser, parse_b: argparse.ArgumentParser):
         """
         Small helper to check pseudo-equality of parsed arguments on `ArgumentParser` instances.
         """
-        self.assertEqual(len(parse_a._actions), len(parse_b._actions))  # pylint: disable=protected-access
+        self.assertEqual(
+            len(parse_a._actions), len(parse_b._actions)
+        )  # pylint: disable=protected-access
         for x, y in zip(parse_a._actions, parse_b._actions):  # pylint: disable=protected-access
             xx = {k: v for k, v in vars(x).items() if k != "container"}
             yy = {k: v for k, v in vars(y).items() if k != "container"}
@@ -175,5 +170,6 @@ def test_namespaces_are_equivalent_str_boolean_int(self):
         build_args_namespace = argparse.Namespace(**build_args_as_dict)
         self.assertNotEqual(build_args_namespace, parsed_args)
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
     unittest.main()