This is an automated email from the ASF dual-hosted git repository.
masahi pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git
The following commit(s) were added to refs/heads/main by this push:
new 0d46cf7 Implement Keras Conv1D (#7035)
0d46cf7 is described below
commit 0d46cf7d15ba1494f302084715db24441aae953f
Author: Matthew Brookhart <[email protected]>
AuthorDate: Fri Dec 4 16:56:31 2020 -0700
Implement Keras Conv1D (#7035)
---
python/tvm/relay/frontend/keras.py | 85 ++++++++++++++++++++++++++++-
tests/python/frontend/keras/test_forward.py | 15 +++++
2 files changed, 98 insertions(+), 2 deletions(-)
diff --git a/python/tvm/relay/frontend/keras.py
b/python/tvm/relay/frontend/keras.py
index b5085d3..4bdca2c 100644
--- a/python/tvm/relay/frontend/keras.py
+++ b/python/tvm/relay/frontend/keras.py
@@ -267,6 +267,81 @@ def _convert_dense(inexpr, keras_layer, etab):
return out
+def _convert_convolution1d(inexpr, keras_layer, etab):
+ _check_data_format(keras_layer)
+ weightList = keras_layer.get_weights()
+ weight = weightList[0]
+
+ if etab.data_layout == "NWC":
+ kernel_layout = "WIO"
+ else:
+ kernel_layout = "OIW"
+ msg = (
+ "Kernel layout with {} is not supported for operator Convolution1D
"
+ "in frontend Keras."
+ )
+ raise tvm.error.OpAttributeUnImplemented(msg.format(etab.data_layout))
+
+ is_deconv = type(keras_layer).__name__ == "Conv1DTranspose"
+
+ if is_deconv:
+ if kernel_layout == "OIW":
+ weight = weight.transpose([2, 0, 1])
+ kernel_w, n_filters, _ = weight.shape
+ else:
+ kernel_w, _, n_filters = weight.shape
+
+ dilation_rate = keras_layer.dilation_rate
+ if isinstance(dilation_rate, (list, tuple)):
+ dilation = [dilation_rate[0]]
+ else:
+ dilation = [dilation_rate]
+
+ dilated_kernel_w = (kernel_w - 1) * dilation[0] + 1
+ stride_w = keras_layer.strides[0]
+ params = {
+ "weight": etab.new_const(weight),
+ "kernel_size": [kernel_w],
+ "strides": [stride_w],
+ "dilation": dilation,
+ "padding": [0],
+ "data_layout": etab.data_layout,
+ "kernel_layout": kernel_layout,
+ }
+ params["channels"] = n_filters
+
+ if keras_layer.padding == "valid":
+ pass
+ # calculate the padding values
+ elif keras_layer.padding == "same":
+ in_w = keras_layer.input_shape[1]
+ pad_w = _get_pad_pair(in_w, dilated_kernel_w, stride_w)
+ params["padding"] = [pad_w[0], pad_w[1]]
+ else:
+ msg = "Padding with {} is not supported for operator Convolution3D "
"in frontend Keras."
+ raise
tvm.error.OpAttributeUnImplemented(msg.format(keras_layer.padding))
+
+ if is_deconv:
+ out = _op.nn.conv1d_transpose(data=inexpr, **params)
+ else:
+ out = _op.nn.conv1d(data=inexpr, **params)
+
+ channel_axis = -1 if etab.data_layout == "NWC" else 1
+ if keras_layer.use_bias:
+ bias = etab.new_const(weightList[1])
+ out = _op.nn.bias_add(out, bias, channel_axis)
+
+ # defuse activation
+ if sys.version_info.major < 3:
+ act_type = keras_layer.activation.func_name
+ else:
+ act_type = keras_layer.activation.__name__
+ if act_type != "linear":
+ out = _convert_activation(out, act_type, etab)
+
+ return out
+
+
def _convert_convolution(inexpr, keras_layer, etab):
_check_data_format(keras_layer)
is_deconv = type(keras_layer).__name__ == "Conv2DTranspose"
@@ -968,7 +1043,8 @@ _convert_map = {
# 'GlobalMaxPooling1D' : _convert_pooling,
# 'Cropping1D' : _convert_cropping,
# 'UpSampling1D' : _convert_upsample,
- # 'Conv1D' : _convert_convolution1d,
+ "Conv1D": _convert_convolution1d,
+ # "Conv1DTranspose": _convert_convolution1d,
"Conv3D": _convert_convolution3d,
"Conv3DTranspose": _convert_convolution3d,
# 'SeparableConv3D' : _convert_convolution3d,
@@ -1102,7 +1178,12 @@ def from_keras(model, shape=None, layout="NCHW"):
etab = ExprTable()
# Set global data format.
- assert layout in ["NCHW", "NHWC", "NDHWC"], "Layout must be one of 'NCHW',
NHWC or NDHWC"
+ assert layout in [
+ "NWC",
+ "NCHW",
+ "NHWC",
+ "NDHWC",
+ ], "Layout must be one of 'NWC', 'NCHW', NHWC or NDHWC"
etab.data_layout = layout
for keras_layer in model.layers:
if isinstance(keras_layer, input_layer_class):
diff --git a/tests/python/frontend/keras/test_forward.py
b/tests/python/frontend/keras/test_forward.py
index 251c887..05d8904 100644
--- a/tests/python/frontend/keras/test_forward.py
+++ b/tests/python/frontend/keras/test_forward.py
@@ -228,6 +228,21 @@ class TestKeras:
keras_model = keras.models.Model(data, y)
verify_keras_frontend(keras_model)
+ def test_forward_conv1d(self, keras):
+ data = keras.layers.Input(shape=(32, 3))
+ conv_funcs = [
+ keras.layers.Conv1D(filters=10, kernel_size=(3,), strides=(2,),
padding="same"),
+ keras.layers.Conv1D(filters=10, kernel_size=(3,),
dilation_rate=(2,), padding="same"),
+ keras.layers.Conv1D(filters=1, kernel_size=(3,), padding="valid",
use_bias=False),
+ keras.layers.Conv1D(filters=10, kernel_size=(2,), padding="valid"),
+ # Enable when relay conv1dtranspose handles NWC
+ # keras.layers.Conv1DTranspose(filters=10, kernel_size=(3),
padding="valid"),
+ ]
+ for conv_func in conv_funcs:
+ x = conv_func(data)
+ keras_model = keras.models.Model(data, x)
+ verify_keras_frontend(keras_model, layout="NWC")
+
def test_forward_conv(self, keras):
data = keras.layers.Input(shape=(32, 32, 3))
conv_funcs = [
