def test_large_seq2col_gpu_against_cpu(nW):
cupy_ops = CupyOps()
numpy_ops = NumpyOps()
# Use array with a large enough batch to require multiple
# CUDA grids.
batch_size = 128 * 128 * 2 # threads per block * blocks * 2
X = numpy_ops.xp.random.randn(batch_size * 2).astype("float32").reshape(
-1, 2)
X_gpu = cupy_ops.asarray2f(X)
# Use somewhat interesting sequence lengths.
lengths = numpy_ops.asarray1i([1, 4, 2, 1] * (batch_size // 8))
lengths_gpu = cupy_ops.asarray1i(lengths)
cols = numpy_ops.seq2col(X, nW=nW, lengths=lengths)
cols_gpu = cupy_ops.seq2col(X_gpu, nW=nW, lengths=lengths_gpu)
assert_allclose(cols, cols_gpu.get())
def set_backend(name, gpu_id):
global CONFIG
if name == "jax":
set_current_ops(JaxOps())
CONFIG = CONFIG.replace("PyTorch", "")
else:
if gpu_id == -1:
set_current_ops(NumpyOps())
else:
set_current_ops(CupyOps())
CONFIG = CONFIG.replace("LSTM.v1", "PyTorchLSTM.v1")
def set_backend(name, gpu_id):
global CONFIG
if name == "generic":
set_current_ops(Ops())
else:
if gpu_id == -1:
set_current_ops(NumpyOps(use_blis=True))
else:
set_current_ops(CupyOps())
if name == "pytorch":
import torch
torch.set_num_threads(1)
CONFIG = CONFIG.replace("LSTM.v1", "PyTorchLSTM.v1")
def set_backend(name, gpu_id):
if gpu_id == -1:
set_current_ops(NumpyOps())
else:
set_current_ops(CupyOps())
CONFIG = CONFIG.replace("LSTM.v1", "PyTorchLSTM.v1")
from thinc.api import LSTM
import inspect
from .. import strategies
from ..strategies import ndarrays_of_shape
MAX_EXAMPLES = 10
VANILLA_OPS = Ops(numpy)
NUMPY_OPS = NumpyOps()
BLIS_OPS = NumpyOps(use_blis=True)
CPU_OPS = [NUMPY_OPS, VANILLA_OPS]
XP_OPS = [NUMPY_OPS]
if CupyOps.xp is not None:
XP_OPS.append(CupyOps())
ALL_OPS = XP_OPS + [VANILLA_OPS]
@pytest.mark.parametrize("op", [NumpyOps, CupyOps])
def test_ops_consistency(op):
"""Test that specific ops don't define any methods that are not on the
Ops base class and that all ops methods define the exact same arguments."""
attrs = [m for m in dir(op) if not m.startswith("_")]
for attr in attrs:
assert hasattr(Ops, attr)
method = getattr(op, attr)
if hasattr(method, "__call__"):
sig = inspect.signature(method)
params = [p for p in sig.parameters][1:]
base_sig = inspect.signature(getattr(Ops, attr))