Current Progress: After final design presentation
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@@ -1,50 +1,57 @@
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import jax
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import jax.numpy as jnp
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from jax import jit, vmap
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from time_utils import using_cprofile
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from time import time
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#
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import numpy as np
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@jit
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def fx(x):
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return jnp.arange(x, x + 10)
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#
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#
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# # @jit
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# def fy(z):
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# z1, z2 = z, z + 1
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# vmap_fx = vmap(fx)
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# return vmap_fx(z1, z2)
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#
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# @jit
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# def test_while(num, init_val):
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# def cond_fun(carry):
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# i, cumsum = carry
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# return i < num
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#
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# def body_fun(carry):
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# i, cumsum = carry
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# cumsum += i
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# return i + 1, cumsum
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#
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# return jax.lax.while_loop(cond_fun, body_fun, (0, init_val))
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def jax_mutate(seed, x):
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noise = jax.random.normal(seed, x.shape) * 0.1
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return x + noise
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def numpy_mutate(x):
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noise = np.random.normal(size=x.shape) * 0.1
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return x + noise
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# @using_cprofile
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def jax_mutate_population(seed, pop_x):
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seeds = jax.random.split(seed, len(pop_x))
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func = vmap(jax_mutate, in_axes=(0, 0))
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return func(seeds, pop_x)
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def numpy_mutate_population(pop_x):
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return np.stack([numpy_mutate(x) for x in pop_x])
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def numpy_mutate_population_vmap(pop_x):
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noise = np.random.normal(size=pop_x.shape) * 0.1
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return pop_x + noise
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def main():
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print(fx(1))
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seed = jax.random.PRNGKey(0)
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i = 10
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while i < 200000:
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pop_x = jnp.ones((i, 100, 100))
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jax_pop_func = jit(jax_mutate_population).lower(seed, pop_x).compile()
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# vmap_f = vmap(fx, in_axes=(None, 0))
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# vmap_vmap_f = vmap(vmap_f, in_axes=(0, None))
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# a = jnp.array([20,10,30])
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# b = jnp.array([6, 5, 4])
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# res = vmap_vmap_f(a, b)
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# print(res)
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# print(jnp.argmin(res, axis=1))
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tic = time()
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res = jax.device_get(jax_pop_func(seed, pop_x))
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jax_time = time() - tic
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tic = time()
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res = numpy_mutate_population(pop_x)
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numpy_time = time() - tic
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tic = time()
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res = numpy_mutate_population_vmap(pop_x)
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numpy_time_vmap = time() - tic
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# print(f'POP_SIZE: {i} | JAX: {jax_time:.4f} | Numpy: {numpy_time:.4f} | Speedup: {numpy_time / jax_time:.4f}')
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print(f'POP_SIZE: {i} | JAX: {jax_time:.4f} | Numpy: {numpy_time:.4f} | Numpy Vmap: {numpy_time_vmap:.4f}')
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i = int(i * 1.3)
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if __name__ == '__main__':
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main()
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