def test_convnet(ctx):
hint = util.divup(64, sqrt(ctx.num_workers))
images = expr.eager(
expr.ones((N_IMGS, ) + IMG_SIZE,
tile_hint=(N_IMGS, N_COLORS, hint, hint)))
w1 = expr.eager(
expr.ones((N_FILTERS, N_COLORS) + FILTER_SIZE, tile_hint=ONE_TILE))
conv1 = stencil.stencil(images, w1, 2)
pool1 = stencil.maxpool(conv1)
w2 = expr.eager(
expr.ones((N_FILTERS, N_FILTERS) + FILTER_SIZE, tile_hint=ONE_TILE))
conv2 = stencil.stencil(pool1, w2, 2)
pool2 = stencil.maxpool(conv2)
w3 = expr.eager(
expr.ones((N_FILTERS, N_FILTERS) + FILTER_SIZE, tile_hint=ONE_TILE))
conv3 = stencil.stencil(pool2, w3, 2)
pool3 = stencil.maxpool(conv3)
util.log_info(pool3.shape)
def _(): conv1 = stencil.stencil(images, w1, 2) pool1 = stencil.maxpool(conv1) conv2 = stencil.stencil(pool1, w2, 2) pool2 = stencil.maxpool(conv2) conv3 = stencil.stencil(pool2, w3, 2) pool3 = stencil.maxpool(conv3) expr.force(pool3)
def _():
conv1 = stencil.stencil(images, w1, 2)
pool1 = stencil.maxpool(conv1)
conv2 = stencil.stencil(pool1, w2, 2)
pool2 = stencil.maxpool(conv2)
conv3 = stencil.stencil(pool2, w3, 2)
pool3 = stencil.maxpool(conv3)
pool3.evaluate()
def _():
conv1 = stencil.stencil(images, w1, 2)
pool1 = stencil.maxpool(conv1)
conv2 = stencil.stencil(pool1, w2, 2)
pool2 = stencil.maxpool(conv2)
conv3 = stencil.stencil(pool2, w3, 2)
pool3 = stencil.maxpool(conv3)
expr.force(pool3)
def test_convnet(ctx):
hint = util.divup(64, sqrt(ctx.num_workers))
images = expr.eager(expr.ones((N_IMGS,) + IMG_SIZE,
tile_hint=(N_IMGS, N_COLORS, hint, hint)))
w1 = expr.eager(expr.ones((N_FILTERS, N_COLORS) + FILTER_SIZE,
tile_hint=ONE_TILE))
conv1 = stencil.stencil(images, w1, 2)
pool1 = stencil.maxpool(conv1)
w2 = expr.eager(expr.ones((N_FILTERS, N_FILTERS) + FILTER_SIZE,
tile_hint=ONE_TILE))
conv2 = stencil.stencil(pool1, w2, 2)
pool2 = stencil.maxpool(conv2)
w3 = expr.eager(expr.ones((N_FILTERS, N_FILTERS) + FILTER_SIZE,
tile_hint=ONE_TILE))
conv3 = stencil.stencil(pool2, w3, 2)
pool3 = stencil.maxpool(conv3)
util.log_info(pool3.shape)
