eric-haibin-lin commented on a change in pull request #14830: [WIP] Use env var
to enforce safe accumulation in ReduceAxesCompute
URL: https://github.com/apache/incubator-mxnet/pull/14830#discussion_r281773490
##########
File path: tests/python/unittest/test_operator.py
##########
@@ -3421,51 +3421,57 @@ def l2norm(input_data, axis=0, keepdims=True):
epsilon = 1e-3
acc_type = {np.float16: np.float32, np.float32: np.float32, np.float64:
np.float64,
np.int32: np.int32, np.int64: np.int64}
+ dtype_to_str = {np.float16: 'float16', np.float32: 'float32', np.float64:
'float64',
+ np.int32: 'int32', np.int64: 'int64'}
is_windows = sys.platform.startswith('win')
- for order in [1, 2]:
- for dtype in [np.float16, np.float32, np.float64, np.int32, np.int64]:
- for i in range(in_data_dim):
- for out_dtype in ['float32', 'float64', 'int32', 'int64']:
- if (dtype == np.int32 or dtype == np.int64) and ('int' not
in out_dtype or is_windows):
- continue
- if dtype != np.int32 and dtype != np.int64 and 'int' in
out_dtype:
- continue
- backward_dtype = np.float32 if out_dtype == 'float32' else
np.float64
- skip_backward = 'int' in out_dtype
- print(order, dtype, i, out_dtype, in_shape)
- in_data = np.random.uniform(-1, 1,
in_shape).astype(acc_type[dtype])
- in_data[abs(in_data) < epsilon] = 2 * epsilon
- norm_sym = mx.symbol.norm(data=data, ord=order, axis=i,
out_dtype=out_dtype, keepdims=True)
- npy_out = l1norm(in_data, i) if order is 1 else
l2norm(in_data, i)
- npy_out_backward = np.sign(in_data) if order is 1 else
in_data/npy_out
- check_symbolic_forward(norm_sym, [in_data.astype(dtype)],
[npy_out.astype(out_dtype)],
- rtol=1e-3, atol=1e-5, ctx=ctx)
- if not skip_backward:
- check_symbolic_backward(norm_sym,
[in_data.astype(dtype)],
-
[np.ones(npy_out.shape).astype(out_dtype)],
- [npy_out_backward], rtol=1e-3,
atol=1e-5, ctx=ctx,
- dtype=backward_dtype)
- # Disable numeric gradient
https://github.com/apache/incubator-mxnet/issues/11509
- # check gradient
- if dtype is not np.float16 and not skip_backward:
- check_numeric_gradient(norm_sym, [in_data],
numeric_eps=epsilon,
- rtol=1e-1, atol=1e-3,
dtype=backward_dtype)
- if i < in_data_dim-1:
- norm_sym = mx.symbol.norm(data=data, ord=order,
axis=(i, i+1), keepdims=True)
- npy_out = l1norm(in_data, (i, i+1)) if order is 1 else
l2norm(in_data, (i, i+1))
+ for enforce_safe_acc in [True, False]:
+ os.environ["MXNET_ENFORCE_SAFE_ACCUMULATION"] = str(enforce_safe_acc)
+ for order in [1, 2]:
+ for dtype in [np.float16, np.float32, np.float64]:
+ for i in range(in_data_dim):
+ for out_dtype in ['float32', 'float64']:
+ backward_dtype = np.float32 if out_dtype == 'float32'
else np.float64
+ accumulation_type = acc_type[dtype]
+ if not enforce_safe_acc:
+ backward_dtype = dtype
+ out_dtype = dtype_to_str[dtype]
+ accumulation_type = dtype
+ print(dtype, out_dtype, accumulation_type)
Review comment:
remove print
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