Python rand Examples

Example #1

File: cluster_net_test.py Project: TimDettmers/clusterNet2

def test_timer():
    if gpu.lib.pt_clusterNet == gpu.lib.pt_clusterNetCPU: return    
    t = gpu.Timer()
    A = gpu.rand(100,100)
    B = gpu.rand(100,100)
    C = gpu.rand(100,100)
    time = 0

    t.tick()
    for i in range(10):
        gpu.dot(A,B,C)
    time = t.tock()
    assert time > 0

    time = 0
    t.tick("Timer test")
    gpu.dot(A,B,C)
    time = t.tock("Timer test")
    assert time > 0

    accumulative_time = 0
    for i in range(100):
        t.tick('cumulative')
        gpu.dot(A,B,C)
        t.tick('cumulative')
    accumulative_time = t.tock('cumulative')

    assert accumulative_time > 5*time

Example #2

File: cluster_net_test.py Project: HSoleimani-USI/clusterNet2

def test_timer():
    if gpu.lib.pt_clusterNet == gpu.lib.pt_clusterNetCPU: return
    t = gpu.Timer()
    A = gpu.rand(100, 100)
    B = gpu.rand(100, 100)
    C = gpu.rand(100, 100)
    time = 0

    t.tick()
    for i in range(10):
        gpu.dot(A, B, C)
    time = t.tock()
    assert time > 0

    time = 0
    t.tick("Timer test")
    gpu.dot(A, B, C)
    time = t.tock("Timer test")
    assert time > 0

    accumulative_time = 0
    for i in range(100):
        t.tick('cumulative')
        gpu.dot(A, B, C)
        t.tick('cumulative')
    accumulative_time = t.tock('cumulative')

    assert accumulative_time > 5 * time

Example #3

File: cluster_net_test.py Project: HSoleimani-USI/clusterNet2

def test_rand():
    A = gpu.rand(100, 100)
    B = A.tocpu()
    assert np.mean(B) > 0.45 and np.mean(B) < 0.55
    assert np.var(B) > 0.08 and np.var(B) < 0.085

    gpu.setRandomState(1234)
    A1 = gpu.rand(1000, 1000)
    gpu.setRandomState(1234)
    A2 = gpu.rand(1000, 1000)
    B1 = A1.tocpu()
    B2 = A2.tocpu()

    t.assert_array_equal(B1, B2, "Seed not working!")

Example #4

File: cluster_net_test.py Project: TimDettmers/clusterNet2

def test_rand():
    A = gpu.rand(100,100)
    B = A.tocpu()
    assert np.mean(B) > 0.45 and np.mean(B) < 0.55
    assert np.var(B) > 0.08 and np.var(B) < 0.085

    gpu.setRandomState(1234)
    A1 = gpu.rand(1000,1000)
    gpu.setRandomState(1234)
    A2 = gpu.rand(1000,1000)
    B1 = A1.tocpu()
    B2 = A2.tocpu()

    t.assert_array_equal(B1, B2, "Seed not working!")

Example #5

File: gemm_single.py Project: TimDettmers/clusterNet2

@author: tim
'''
import cluster_net as gpu
import cudanet as gpu2



t = gpu.Timer()
dim1 = 16
dim_inner = 1024
dim_outer = 1024

batch_first_mode = True

if batch_first_mode:
    input = gpu.rand(dim1,dim_inner)
    W = gpu.rand(dim_inner,dim_outer)
    output = gpu.rand(dim1,dim_outer)
    input2 = gpu2.random.rand(dim1,dim_inner)
    W2 = gpu2.random.rand(dim_inner,dim_outer)
    output2 = gpu2.random.rand(dim1,dim_outer)
else:    
    input = gpu.rand(dim_inner,dim1)
    W = gpu.rand(dim_outer,dim_inner)
    output = gpu.rand(dim_outer,dim1)
    
    input2 = gpu2.random.rand(dim_inner,dim1)
    W2 = gpu2.random.rand(dim_outer,dim_inner)
    output2 = gpu2.random.rand(dim_outer,dim1)

Example #6

File: matrix_multiplication.py Project: HSoleimani-USI/clusterNet2

'''
Created on Dec 31, 2015

@author: tim
'''
import cluster_net as gpu
import time

t = gpu.Timer()
dim1 = 128
dim_inner = 32
dim_outer = 256
for i in range(1000):
    dim_inner += 32
    A = gpu.rand(dim1, dim_inner)
    B = gpu.rand(dim_inner, dim_outer)
    C = gpu.rand(dim1, dim_outer)

    if dim_inner > 0: iters = 1000
    if dim_inner > 100: iters = 100
    if dim_inner > 1000: iters = 10
    if dim_inner > 3000: iters = 4

    #warmup
    for j in range(2):
        gpu.dot(A, B, C)
    t.tick(str(dim_inner))
    for j in range(iters):
        gpu.dot(A, B, C)
    sec = t.tock(str(dim_inner)) / 1000.
    tilesA = (dim1 / 16) * ((dim_inner / 64) +

Example #7

File: gemm_single.py Project: HSoleimani-USI/clusterNet2

outputreated on Jan 3, 2016

@author: tim
'''
import cluster_net as gpu
import cudanet as gpu2

t = gpu.Timer()
dim1 = 16
dim_inner = 1024
dim_outer = 1024

batch_first_mode = True

if batch_first_mode:
    input = gpu.rand(dim1, dim_inner)
    W = gpu.rand(dim_inner, dim_outer)
    output = gpu.rand(dim1, dim_outer)
    input2 = gpu2.random.rand(dim1, dim_inner)
    W2 = gpu2.random.rand(dim_inner, dim_outer)
    output2 = gpu2.random.rand(dim1, dim_outer)
else:
    input = gpu.rand(dim_inner, dim1)
    W = gpu.rand(dim_outer, dim_inner)
    output = gpu.rand(dim_outer, dim1)

    input2 = gpu2.random.rand(dim_inner, dim1)
    W2 = gpu2.random.rand(dim_outer, dim_inner)
    output2 = gpu2.random.rand(dim_outer, dim1)

mean_time = 0

Example #8

File: matrix_multiplication.py Project: TimDettmers/clusterNet2

'''
Created on Dec 31, 2015

@author: tim
'''
import cluster_net as gpu
import time

t = gpu.Timer()
dim1 = 128
dim_inner = 32
dim_outer = 256
for i in range(1000):
    dim_inner += 32
    A = gpu.rand(dim1,dim_inner)
    B = gpu.rand(dim_inner,dim_outer)
    C = gpu.rand(dim1,dim_outer)
    
    if dim_inner > 0: iters = 1000
    if dim_inner > 100: iters = 100
    if dim_inner > 1000: iters = 10
    if dim_inner > 3000: iters = 4
    
    #warmup
    for j in range(2):
        gpu.dot(A,B,C)
    t.tick(str(dim_inner))
    for j in range(iters):
        gpu.dot(A,B,C)
    sec = t.tock(str(dim_inner))/1000.
    tilesA = (dim1/16)*((dim_inner/64) + (1 if dim_inner % 64 > 0 else 0))