zxybazh commented on code in PR #11797:
URL: https://github.com/apache/tvm/pull/11797#discussion_r910464495
##########
python/tvm/meta_schedule/testing/utils.py:
##########
@@ -77,3 +81,145 @@ def apply_fixed_schedules(
database.commit_tuning_record(tune_rec)
return database
+
+
+def generate_input_data(input_shape: List[int], input_dtype: str) ->
np.ndarray:
+ """Generate input date with given shape and data type.
+
+ Parameters
+ ----------
+ input_shape : List[int]
+ The shape of the input data.
+ input_dtype : str
+ The data type of the input date.
+
+ Returns
+ -------
+ input_data : np.ndarray
+ The generated input data with given shape and data type in numpy
ndarray.
+ """
+ if input_dtype.startswith("float"):
+ return np.random.uniform(size=input_shape).astype(input_dtype)
+ if input_dtype in ["uint8", "int8"]:
+ return np.random.randint(
+ low=0,
+ high=127,
+ size=input_shape,
+ dtype="int32", # TODO(zxybazh): fix the datatype when int8 /
uint8 is supported better
+ )
+ if input_dtype in ["int32", "int64"]:
+ return np.random.randint(low=0, high=10000, size=input_shape,
dtype=input_dtype)
Review Comment:
That's right, for `gpt-2` and `bert` the embedding table is not the same. In
that case we need user input, so I'll just add the low and high as argument in
this function and throw a warning.
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