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from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
from hypothesis import given, settings
import numpy as np
class TestIndexHashOps(serial.SerializedTestCase):
@given(
indices=st.sampled_from([
np.int32, np.int64
]).flatmap(lambda dtype: hu.tensor(min_dim=1, max_dim=1, dtype=dtype)),
seed=st.integers(min_value=0, max_value=10),
modulo=st.integers(min_value=100000, max_value=200000),
**hu.gcs_cpu_only
)
@settings(deadline=10000)
def test_index_hash_ops(self, indices, seed, modulo, gc, dc):
def index_hash(indices):
dtype = np.array(indices).dtype
assert dtype == np.int32 or dtype == np.int64
hashed_indices = []
for index in indices:
hashed = dtype.type(0xDEADBEEF * seed)
indices_bytes = np.array([index], dtype).view(np.int8)
for b in indices_bytes:
hashed = dtype.type(hashed * 65537 + b)
hashed = (modulo + hashed % modulo) % modulo
hashed_indices.append(hashed)
return [hashed_indices]
op = core.CreateOperator("IndexHash",
["indices"], ["hashed_indices"],
seed=seed, modulo=modulo)
self.assertDeviceChecks(dc, op, [indices], [0])
self.assertReferenceChecks(gc, op, [indices], index_hash)
# In-place update
op = core.CreateOperator("IndexHash",
["indices"], ["indices"],
seed=seed, modulo=modulo)
self.assertDeviceChecks(dc, op, [indices], [0])
self.assertReferenceChecks(gc, op, [indices], index_hash)
def test_shape_and_type_inference(self):
with hu.temp_workspace("shape_type_inf_int64"):
net = core.Net('test_net')
net.ConstantFill(
[], "values", shape=[64], dtype=core.DataType.INT64,
)
net.IndexHash(['values'], ['values_output'])
(shapes, types) = workspace.InferShapesAndTypes([net], {})
self.assertEqual(shapes["values_output"], [64])
self.assertEqual(types["values_output"], core.DataType.INT64)
with hu.temp_workspace("shape_type_inf_int32"):
net = core.Net('test_net')
net.ConstantFill(
[], "values", shape=[2, 32], dtype=core.DataType.INT32,
)
net.IndexHash(['values'], ['values_output'])
(shapes, types) = workspace.InferShapesAndTypes([net], {})
self.assertEqual(shapes["values_output"], [2, 32])
self.assertEqual(types["values_output"], core.DataType.INT32)
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