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import numpy as np
from hypothesis import given, settings
import hypothesis.strategies as st
import unittest
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
class TestTile(serial.SerializedTestCase):
@given(M=st.integers(min_value=1, max_value=10),
K=st.integers(min_value=1, max_value=10),
N=st.integers(min_value=1, max_value=10),
tiles=st.integers(min_value=1, max_value=3),
axis=st.integers(min_value=0, max_value=2),
**hu.gcs)
@settings(deadline=10000)
def test_tile(self, M, K, N, tiles, axis, gc, dc):
X = np.random.rand(M, K, N).astype(np.float32)
op = core.CreateOperator(
'Tile', ['X'], 'out',
tiles=tiles,
axis=axis,
)
def tile_ref(X, tiles, axis):
dims = np.asarray([1, 1, 1], dtype=np.int)
dims[axis] = tiles
tiled_data = np.tile(X, dims)
return (tiled_data,)
# Check against numpy reference
self.assertReferenceChecks(gc, op, [X, tiles, axis],
tile_ref)
# Check over multiple devices
self.assertDeviceChecks(dc, op, [X], [0])
# Gradient check wrt X
self.assertGradientChecks(gc, op, [X], 0, [0])
@unittest.skipIf(not workspace.has_gpu_support, "No gpu support")
@given(M=st.integers(min_value=1, max_value=200),
N=st.integers(min_value=1, max_value=200),
tiles=st.integers(min_value=50, max_value=100),
**hu.gcs)
def test_tile_grad(self, M, N, tiles, gc, dc):
X = np.random.rand(M, N).astype(np.float32)
axis = 1
op = core.CreateOperator(
'Tile', ['X'], 'out',
tiles=tiles,
axis=axis,
)
def tile_ref(X, tiles, axis):
dims = np.asarray([1, 1], dtype=np.int)
dims[axis] = tiles
tiled_data = np.tile(X, dims)
return (tiled_data,)
# Check against numpy reference
self.assertReferenceChecks(gc, op, [X, tiles, axis],
tile_ref)
# Check over multiple devices
self.assertDeviceChecks(dc, op, [X], [0])
# Gradient check wrt X
grad_op = core.CreateOperator(
'TileGradient', ['dOut'], 'dX',
tiles=tiles,
axis=axis,
)
dX = np.random.rand(M, N * tiles).astype(np.float32)
self.assertDeviceChecks(dc, grad_op, [dX], [0])
@given(M=st.integers(min_value=1, max_value=10),
K=st.integers(min_value=1, max_value=10),
N=st.integers(min_value=1, max_value=10),
tiles=st.integers(min_value=1, max_value=3),
axis=st.integers(min_value=0, max_value=2),
**hu.gcs)
@settings(deadline=10000)
def test_tilewinput(self, M, K, N, tiles, axis, gc, dc):
X = np.random.rand(M, K, N).astype(np.float32)
tiles_arg = np.array([tiles], dtype=np.int32)
axis_arg = np.array([axis], dtype=np.int32)
op = core.CreateOperator(
'Tile', ['X', 'tiles', 'axis'], 'out',
)
def tile_ref(X, tiles, axis):
dims = np.asarray([1, 1, 1], dtype=np.int)
dims[axis] = tiles
tiled_data = np.tile(X, dims)
return (tiled_data,)
# Check against numpy reference
self.assertReferenceChecks(gc, op, [X, tiles_arg, axis_arg],
tile_ref)
# Check over multiple devices
self.assertDeviceChecks(dc, op, [X, tiles_arg, axis_arg], [0])
# Gradient check wrt X
self.assertGradientChecks(gc, op, [X, tiles_arg, axis_arg], 0, [0])
if __name__ == "__main__":
unittest.main()
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