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https://github.com/ml-explore/mlx.git
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108 lines
2.6 KiB
Python
108 lines
2.6 KiB
Python
# Copyright © 2023-2024 Apple Inc.
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import argparse
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import math
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import random
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import mlx.core as mx
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from time_utils import time_fn
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def bench_gelu():
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def gelu(x):
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return x * (1 + mx.erf(x / math.sqrt(2))) / 2
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x = mx.random.uniform(shape=(1000, 1024))
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def gen_fun(fun):
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def bench_fun(x):
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for _ in range(10):
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x = fun(x)
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return x
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return bench_fun
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time_fn(gen_fun(gelu), x, msg="fixed gelu")
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time_fn(gen_fun(mx.compile(gelu)), x, msg="compiled fixed gelu")
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def randint():
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return random.randint(1, x.shape[0])
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def gen_fun(fun):
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def bench_fun(x, y):
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x = x[: randint()]
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for _ in range(10):
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x = fun(x)
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y = fun(y)
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return x, y
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return bench_fun
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y = mx.random.uniform(shape=(1000, 1024))
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time_fn(gen_fun(gelu), x, y, msg="variable gelu")
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time_fn(gen_fun(mx.compile(gelu)), x, y, msg="compiled variable gelu")
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time_fn(
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gen_fun(mx.compile(gelu, shapeless=True)),
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x,
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y,
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msg="shapeless variable gelu",
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)
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def bench_layernorm():
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weight = mx.random.uniform(shape=(4096,)).astype(mx.float16)
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bias = mx.random.uniform(shape=(4096,)).astype(mx.float16)
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mx.eval(weight, bias)
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def layernorm(x):
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x = x.astype(mx.float32)
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means = mx.mean(x, axis=-1, keepdims=True)
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var = mx.var(x, axis=-1, keepdims=True)
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x = (x - means) * mx.rsqrt(var + 1e-4)
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x = x.astype(mx.float16)
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return weight * x + bias
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x = mx.random.uniform(shape=(1000, 4096)).astype(mx.float16)
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def gen_fun(fun):
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def bench_fun(x):
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for _ in range(10):
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x = fun(x)
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return x
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return bench_fun
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time_fn(gen_fun(layernorm), x, msg="fixed layernorm")
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time_fn(gen_fun(mx.compile(layernorm)), x, msg="compiled fixed layernorm")
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def randint():
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return random.randint(1, x.shape[0])
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def gen_fun(fun):
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def bench_fun(x):
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x = x[: randint()]
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for _ in range(10):
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x = fun(x)
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return x
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return bench_fun
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random.seed(0)
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time_fn(gen_fun(layernorm), x, msg="variable layernorm")
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random.seed(0)
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time_fn(gen_fun(mx.compile(layernorm)), x, msg="compiled variable layernorm")
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random.seed(0)
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time_fn(
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gen_fun(mx.compile(layernorm, shapeless=True)),
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x,
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msg="shapeless variable layernorm",
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)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser("Compile benchmarks.")
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args = parser.parse_args()
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bench_gelu()
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bench_layernorm()
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