def verify_output(self, outs):
outs = convert_uint16_to_float(outs)
self.assertEqual(outs[0].shape, (123, 92))
hist, _ = np.histogram(outs[0], range=(-3, 5))
hist = hist.astype("float32")
hist /= float(outs[0].size)
data = np.random.normal(size=(123, 92), loc=1, scale=2)
hist2, _ = np.histogram(data, range=(-3, 5))
hist2 = hist2.astype("float32")
hist2 /= float(outs[0].size)
self.assertTrue(np.allclose(hist, hist2, rtol=0, atol=0.05),
"hist: " + str(hist) + " hist2: " + str(hist2))
def check_input_and_optput(self,
scope,
place,
inplace,
w1_has_data=False,
w2_has_data=False,
w3_has_data=False):
self.create_selected_rows(scope, place, "W1", w1_has_data)
self.create_selected_rows(scope, place, "W2", w2_has_data)
self.create_selected_rows(scope, place, "W3", w3_has_data)
# create Out Variable
if inplace:
out_var_name = "W1"
else:
out_var_name = "Out"
out = scope.var(out_var_name).get_selected_rows()
# create and run sum operator
sum_op = Operator("sum", X=["W1", "W2", "W3"], Out=out_var_name)
sum_op.run(scope, place)
has_data_w_num = 0
for has_data in [w1_has_data, w2_has_data, w3_has_data]:
if has_data:
has_data_w_num += 1
if has_data_w_num > 0:
self.assertEqual(len(out.rows()), 7)
out_bf16 = np.array(out.get_tensor())
out_fp32 = convert_uint16_to_float(out_bf16)
ref_fp32 = convert_uint16_to_float(
self._get_array(self.rows, self.row_numel)) * has_data_w_num
np.testing.assert_allclose(out_fp32,
ref_fp32,
atol=0,
rtol=0.95e-2)
else:
self.assertEqual(len(out.rows()), 0)
def _check_output(self,
actual,
reference,
bf16=False,
atol=0,
rtol=0.15e-2):
output = actual if bf16 else convert_uint16_to_float(actual)
if bf16:
np.testing.assert_allclose(output, reference, atol=atol, rtol=rtol)
else:
try:
print('Compare with FP32 values:')
np.testing.assert_allclose(output,
reference,
atol=atol,
rtol=rtol)
except AssertionError as e:
print(e)
def test_lookup_results(self):
lookup_result = convert_uint16_to_float(self.result[1])
lookup_ref = _lookup(self.w_fp32, self.ids, self.flat_ids)
self.assertTrue(np.array_equal(lookup_result, lookup_ref))
def test_embedding_weights(self):
result = convert_uint16_to_float(self.result[0])
self.assertTrue(np.array_equal(self.w_fp32, result))
def _check_output(self, reference, result_array):
result_array_fp32 = convert_uint16_to_float(result_array)
np.testing.assert_allclose(result_array_fp32, reference, rtol=1.5e-2)
def check_output(self, actual_bf16, reference, atol=0, rtol=0.15e-2):
actual_fp32 = convert_uint16_to_float(actual_bf16)
np.testing.assert_allclose(actual_fp32,
reference,
atol=atol,
rtol=rtol)
