This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/master by this push:
new 99c4f9d [TENSORFLOW]reduce ops updated (#5180)
99c4f9d is described below
commit 99c4f9d52a12a3fe83c5caa03cd7f1d827f5b5f0
Author: Samuel <siju.sam...@huawei.com>
AuthorDate: Fri Apr 10 07:26:47 2020 +0530
[TENSORFLOW]reduce ops updated (#5180)
---
python/tvm/relay/frontend/tensorflow.py | 45 +++++----
tests/python/frontend/tensorflow/test_forward.py | 123 ++++++-----------------
2 files changed, 59 insertions(+), 109 deletions(-)
diff --git a/python/tvm/relay/frontend/tensorflow.py
b/python/tvm/relay/frontend/tensorflow.py
index 84318c3..77dbcb5 100644
--- a/python/tvm/relay/frontend/tensorflow.py
+++ b/python/tvm/relay/frontend/tensorflow.py
@@ -1094,6 +1094,14 @@ def _reduce(op):
ignores=['name', 'Tidx'])([inputs[0]], attr)
return _impl
+def _euclidean_norm():
+ def _impl(inputs, attr, params, mod):
+ axis = tuple(_get_list_param(params, inputs[1]))
+ keep_dims = bool(attr.get('keep_dims', False))
+ return _op.sqrt(_op.cast(_op.reduce.sum(_op.multiply(inputs[0],
inputs[0]),
+ axis, keep_dims), "float32"))
+ return _impl
+
def _square():
def _impl(inputs, attr, params, mod):
return _op.multiply(inputs[0], inputs[0])
@@ -1686,8 +1694,8 @@ _freezed_graph_pruned_op_list = ['ReadVariableOp',
'ResourceGather', 'Variable',
_convert_map = {
'Abs' : AttrCvt('abs'),
'Add' : _elemwise('add'),
- 'AddV2' : _elemwise('add'),
'AddN' : _add_n(),
+ 'AddV2' : _elemwise('add'),
'All' : _reduce('all'),
'Any' : _reduce('any'),
'ArgMax' : _argx(_op.argmax, 'argmax'),
@@ -1710,16 +1718,18 @@ _convert_map = {
'Concat' : _concat(),
'ConcatV2' : _concatV2(),
'Conv2D' : _conv('conv'),
- 'Conv3D' : _conv3d('conv'),
'Conv2DBackpropInput' : _conv('conv_transpose'),
+ 'Conv3D' : _conv3d('conv'),
+ 'Cos' : AttrCvt('cos'),
'CropAndResize' : _crop_and_resize(),
'DecodeJpeg' : _decode_image(),
- 'DepthwiseConv2dNative' : _conv('depthwise'),
'DepthToSpace' : _depth_to_space(),
+ 'DepthwiseConv2dNative' : _conv('depthwise'),
'Dilation2D' : _dilation2d(),
- 'Equal' : _broadcast('equal'),
'Elu' : _elu(),
+ 'Equal' : _broadcast('equal'),
'Erf' : AttrCvt('erf'),
+ 'EuclideanNorm' : _euclidean_norm(),
'Exp' : AttrCvt('exp'),
'ExpandDims' : _expand_dims(),
'Fill' : _fill(),
@@ -1743,19 +1753,16 @@ _convert_map = {
'LessEqual' : _broadcast('less_equal'),
'Log' : AttrCvt('log'),
'Log1p' : _log1p(),
- 'Tan' : AttrCvt('tan'),
- 'Cos' : AttrCvt('cos'),
- 'Sin' : AttrCvt('sin'),
'LogicalAnd' : _logical('logical_and'),
- 'LogicalOr' : _logical('logical_or'),
'LogicalNot' : _logical('logical_not'),
+ 'LogicalOr' : _logical('logical_or'),
'LogSoftmax' : AttrCvt('log_softmax'),
'LRN' : _lrn(),
'MatMul' : _matmul(),
'Max' : _reduce('max'),
+ 'Maximum' : _elemwise('maximum'),
'MaxPool' : _pooling('max_pool'),
'MaxPool3D' : _pool3d('max_pool3d'),
- 'Maximum' : _elemwise('maximum'),
'Mean' : _mean(),
'Min' : _reduce('min'),
'Minimum' : _elemwise('minimum'),
@@ -1767,14 +1774,6 @@ _convert_map = {
'NotEqual' : _broadcast('not_equal'),
'OneHot' : _one_hot(),
'Pack' : _pack(),
- 'TensorArrayV3' : _tensor_array(),
- 'TensorArrayScatterV3' : _tensor_array_scatter(),
- 'TensorArrayGatherV3' : _tensor_array_gather(),
- 'TensorArraySizeV3' : _tensor_array_size(),
- 'TensorArrayWriteV3' : _tensor_array_write(),
- 'TensorArrayReadV3' : _tensor_array_read(),
- 'TensorArraySplitV3' : _tensor_array_split(),
- 'TensorArrayConcatV3' : _tensor_array_concat(),
'Pad' : _pad('Pad'),
'PadV2' : _pad('PadV2'),
'Pow' : _elemwise('power'),
@@ -1785,8 +1784,8 @@ _convert_map = {
'Relu' : AttrCvt('relu'),
'Relu6' : _relu6(),
'Reshape' : _reshape(),
- 'ResizeBilinear' : _resize('bilinear'),
'ResizeBicubic' : _resize('bilinear'),
+ 'ResizeBilinear' : _resize('bilinear'),
'ResizeNearestNeighbor' : _resize('nearest_neighbor'),
'ReverseV2' : _reverse_v2(),
'RightShift' : AttrCvt('right_shift'),
@@ -1797,6 +1796,7 @@ _convert_map = {
'Shape' : _shape(),
'Sigmoid' : AttrCvt('sigmoid'),
'Sign' : AttrCvt('sign'),
+ 'Sin' : AttrCvt('sin'),
'Size' : _size(),
'Slice' : _slice(),
'Softmax' : _softmax(),
@@ -1813,7 +1813,16 @@ _convert_map = {
'StridedSlice' : _stridedSlice(),
'Sub' : _elemwise('subtract'),
'Sum' : _sum(),
+ 'Tan' : AttrCvt('tan'),
'Tanh' : AttrCvt('tanh'),
+ 'TensorArrayConcatV3' : _tensor_array_concat(),
+ 'TensorArrayGatherV3' : _tensor_array_gather(),
+ 'TensorArrayReadV3' : _tensor_array_read(),
+ 'TensorArrayScatterV3' : _tensor_array_scatter(),
+ 'TensorArraySizeV3' : _tensor_array_size(),
+ 'TensorArraySplitV3' : _tensor_array_split(),
+ 'TensorArrayV3' : _tensor_array(),
+ 'TensorArrayWriteV3' : _tensor_array_write(),
'Tile' : _tile(),
'TopKV2' : _topk(),
'Transpose' : _transpose(),
diff --git a/tests/python/frontend/tensorflow/test_forward.py
b/tests/python/frontend/tensorflow/test_forward.py
index 5c0391f..35a3466 100644
--- a/tests/python/frontend/tensorflow/test_forward.py
+++ b/tests/python/frontend/tensorflow/test_forward.py
@@ -1029,28 +1029,6 @@ def test_forward_argminmax():
_test_argx(tf.argmax, data=data, axis=axis)
_test_argx(tf.argmin, data=data, axis=axis)
-#######################################################################
-# Reduce
-# ------
-
-
-def _test_reduce(func, data, **kwargs):
- """ One iteration of a reduce operation"""
-
- with tf.Graph().as_default():
- inp = array_ops.placeholder(
- shape=data.shape, dtype=data.dtype, name="c0")
- func(inp, name="reducex0", **kwargs)
-
- compare_tf_with_tvm(data, 'c0:0', 'reducex0:0')
-
-
-def test_forward_reduce():
- data = np.random.uniform(size=(8, 4, 9)).astype('float32')
- _test_reduce(tf.reduce_sum, data=data)
- _test_reduce(tf.reduce_sum, data=data, axis=0)
- _test_reduce(tf.reduce_sum, data=data, axis=(0, 1))
-
#######################################################################
# Variable
@@ -2845,55 +2823,42 @@ def test_forward_size():
check_size((10,))
#######################################################################
-# All, Any, Max, Min
-# ------------------
-
-def test_forward_reduce_all():
- """Test the All operator."""
- np_data = np.random.choice([True, False], size=(5, 7, 11))
- tf.reset_default_graph()
- with tf.Graph().as_default():
- in_data = tf.placeholder(tf.bool, (5, 7, 11), name="in_data")
- tf.reduce_all(in_data, name="all")
- compare_tf_with_tvm([np_data], ['in_data:0'], 'all:0')
-
-def test_forward_reduce_any():
- """Test the Any operator."""
- np_data = np.random.choice([True, False], size=(5, 7, 11))
- tf.reset_default_graph()
- with tf.Graph().as_default():
- in_data = tf.placeholder(tf.bool, (5, 7, 11), name="in_data")
- tf.reduce_any(in_data, name="any")
- compare_tf_with_tvm([np_data], ['in_data:0'], 'any:0')
+# All, Any, Max, Min, Prod, variance, std, logsumexp, euclidean_norm
+# ------------------------------------------------------------------
-def test_forward_reduce_max():
- def check_max(ishape, axis, keepdims, dtype):
- tf.reset_default_graph()
- np_data = np.random.uniform(size=ishape).astype(dtype)
- with tf.Graph().as_default():
- in_data = tf.placeholder(dtype, name="in_data")
- tf.math.reduce_max(in_data, axis=axis,
- keepdims=keepdims, name="reduce_max")
- compare_tf_with_tvm([np_data], ['in_data:0'], 'reduce_max:0')
-
- check_max((10, 8, 16, 32), axis=(-1), keepdims=True, dtype="int32")
- check_max((10, 8, 16, 32), axis=(2, 3), keepdims=True, dtype="float32")
- check_max((10, 8, 16, 32), axis=(1, 2), keepdims=True, dtype='float32')
-
-
-def test_forward_reduce_min():
- def check_min(ishape, axis, keepdims, dtype):
+def test_forward_reduce():
+ def _check_op(tf_op, ishape, axis, keepdims, dtype="float32"):
tf.reset_default_graph()
- np_data = np.random.uniform(size=ishape).astype(dtype)
+ if dtype == "bool":
+ np_data = np.random.choice([True, False], size=ishape)
+ else:
+ np_data = np.random.uniform(size=ishape).astype(dtype)
+ if tf_op == tf.math.reduce_prod:
+ axis = 1
+ np_data = np_data.reshape(1, -1)
with tf.Graph().as_default():
in_data = tf.placeholder(dtype, name="in_data")
- tf.math.reduce_min(in_data, axis=axis,
- keepdims=keepdims, name="reduce_max")
- compare_tf_with_tvm([np_data], ['in_data:0'], 'reduce_max:0')
-
- check_min((10, 8, 16, 32), axis=(-1), keepdims=True, dtype="int32")
- check_min((10, 8, 16, 32), axis=(2, 3), keepdims=True, dtype="float32")
- check_min((10, 8, 16, 32), axis=(1, 2), keepdims=True, dtype='float32')
+ reduce_op = tf_op(in_data, axis=axis,
+ keepdims=keepdims, name="reduce_std")
+ compare_tf_with_tvm([np_data], ['in_data:0'], reduce_op.name)
+
+ def _test_math_op(op, dtypes=["int32", "float32"]):
+ for dtype in dtypes:
+ _check_op(op, (3, 10), axis=(-1), keepdims=False, dtype=dtype)
+ _check_op(op, (8, 16, 32), axis=(-1), keepdims=False, dtype=dtype)
+ _check_op(op, (1, 8, 8, 3), axis=(2, 3), keepdims=True,
dtype=dtype)
+ _check_op(op, (2, 3, 10, 10), axis=(1, 2), keepdims=True,
dtype=dtype)
+
+ _test_math_op(tf.math.reduce_all, dtypes=["bool"])
+ _test_math_op(tf.math.reduce_any, dtypes=["bool"])
+ _test_math_op(tf.math.reduce_max)
+ _test_math_op(tf.math.reduce_min)
+ _test_math_op(tf.math.reduce_prod)
+ _test_math_op(tf.math.reduce_variance)
+ _test_math_op(tf.math.reduce_std, dtypes=["float32"])
+ _test_math_op(tf.math.reduce_logsumexp, dtypes=["float32"])
+ if package_version.parse(tf.VERSION) >= package_version.parse('1.15.0'):
+ _test_math_op(tf.math.reduce_euclidean_norm)
#######################################################################
# Relational operators
@@ -2943,26 +2908,6 @@ def test_forward_expand_dims():
#######################################################################
-# Prod
-# ----
-def _test_forward_reduce_prod(shape, axis, keepdims):
- inp_array1 = np.random.uniform(-5, 5, size=shape).astype(np.float32)
- with tf.Graph().as_default():
- in1 = tf.placeholder(shape=inp_array1.shape, dtype=inp_array1.dtype)
- out = tf.math.reduce_prod(in1, axis, keepdims)
- compare_tf_with_tvm(inp_array1, in1.name, out.name)
-
-
-def test_forward_reduce_prod():
- _test_forward_reduce_prod((5,), 0, False)
- _test_forward_reduce_prod((5, 5), 0, False)
- _test_forward_reduce_prod((5, 5), 1, False)
- _test_forward_reduce_prod((5,), 0, True)
- _test_forward_reduce_prod((5, 5), 0, True)
- _test_forward_reduce_prod((5, 5), 1, True)
-
-
-#######################################################################
# Maximum, Minimum
# ----------------
def test_forward_maximum():
@@ -3295,10 +3240,6 @@ if __name__ == '__main__':
test_forward_argminmax()
test_forward_reduce()
test_forward_mean()
- test_forward_reduce_prod()
- test_forward_reduce_all()
- test_forward_reduce_any()
- test_forward_reduce_min()
# General
test_forward_multi_input()
