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Revert "[CI] Tensorflow version support upgrade from 2.1.0 to 2.3.1" #6773

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Revert "[CI] Tensorflow version support upgrade from 2.1.0 to 2.3.1" #6773

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2 changes: 1 addition & 1 deletion docker/install/ubuntu_install_tensorflow.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -20,4 +20,4 @@ set -e
set -u
set -o pipefail

pip3 install tensorflow==2.3.1 keras==2.3.1 h5py
pip3 install tensorflow==2.1.0 keras==2.3.1 h5py
4 changes: 2 additions & 2 deletions python/tvm/relay/frontend/tensorflow.py
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Expand Up @@ -1334,7 +1334,7 @@ def _impl(inputs, attr, params, mod):
op_name="batch_norm",
transforms={"scale_after_normalization": "scale", "variance_epsilon": "epsilon"},
extras={"axis": axis},
ignores=["data_format", "U", "exponential_avg_factor"],
ignores=["data_format", "U"],
disables=["momentum"],
)(inputs, attr)

Expand Down Expand Up @@ -1364,7 +1364,7 @@ def _impl(inputs, attr, params, mod):
op_name="batch_norm",
transforms={"scale_after_normalization": "scale", "variance_epsilon": "epsilon"},
extras={"axis": axis},
ignores=["data_format", "exponential_avg_factor"],
ignores=["data_format"],
disables=["momentum"],
)(new_inputs, attr)

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6 changes: 3 additions & 3 deletions tests/python/frontend/tensorflow/test_forward.py
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Expand Up @@ -3644,7 +3644,7 @@ def _test_math_op(op, dtypes=["int32", "float32"]):
_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, dtypes=["float32"])
_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"):
Expand Down Expand Up @@ -3855,11 +3855,11 @@ def test_forward_unravel_index():
_test_forward_unravel_index([x, y])

x = np.array([0, 1, 2, 5])
y = np.array([2, 3])
y = np.array([2, 2])
_test_forward_unravel_index([x, y])

x = np.array([0, 1, 2, 5])
y = np.array([6])
y = np.array([2])
_test_forward_unravel_index([x, y])

x = np.array([102, 300, 16])
Expand Down