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fix comments ngraph api - master (#3519)

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* fix comments ngraph api

* remove whitespace

* fixes

Co-authored-by: Nikolay Tyukaev <ntyukaev_lo@jenkins.inn.intel.com>
This commit is contained in:
Nikolay Tyukaev 2021-02-02 07:01:58 +03:00 committed by GitHub
parent a6ea479688
commit 0ecc360664
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GPG Key ID: 4AEE18F83AFDEB23
18 changed files with 308 additions and 317 deletions
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5
docs/doxygen/ngraph_py_api.xml
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@ -37,10 +37,7 @@ limitations under the License.
<tab type="user" title="DL Streamer API Reference" url="https://openvinotoolkit.github.io/dlstreamer_gst/"/>
<tab type="user" title="nGraph С++ API Reference" url="../ngraph_cpp_api/annotated.html"/>
<!-- nGraph Python API Reference -->
<tab type="files" visible="yes" title="nGraph Python API Reference">
<tab type="filelist" visible="yes" title="nGraph Python API Reference" intro=""/>
<tab type="globals" visible="yes" title="" intro=""/>
</tab>
<tab type="filelist" visible="yes" title="nGraph Python API Reference" intro=""/>
</tab>
<!-- Chinese docs -->
<tab type="user" title="中文文件" url="https://docs.openvinotoolkit.org/cn/index.html"/>

2
ngraph/python/src/ngraph/__init__.py
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@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
"""! ngraph module namespace, exposing factory functions for all ops and other classes."""
"""ngraph module namespace, exposing factory functions for all ops and other classes."""
# noqa: F401
from pkg_resources import get_distribution, DistributionNotFound

8
ngraph/python/src/ngraph/exceptions.py
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@ -13,16 +13,16 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
"""! ngraph exceptions hierarchy. All exceptions are descendants of NgraphError."""
"""ngraph exceptions hierarchy. All exceptions are descendants of NgraphError."""
class NgraphError(Exception):
"""! Base class for Ngraph exceptions."""
"""Base class for Ngraph exceptions."""
class UserInputError(NgraphError):
"""! User provided unexpected input."""
"""User provided unexpected input."""
class NgraphTypeError(NgraphError, TypeError):
"""! Type mismatch error."""
"""Type mismatch error."""

4
ngraph/python/src/ngraph/helpers.py
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@ -13,14 +13,14 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
"""! nGraph helper functions."""
"""nGraph helper functions."""
from ngraph.impl import Function
from openvino.inference_engine import IENetwork
def function_from_cnn(cnn_network: IENetwork) -> Function:
"""! Get nGraph function from Inference Engine CNN network."""
"""Get nGraph function from Inference Engine CNN network."""
capsule = cnn_network._get_function_capsule()
ng_function = Function.from_capsule(capsule)
return ng_function

2
ngraph/python/src/ngraph/impl/op/__init__.py
View File

@ -24,7 +24,7 @@ import numpy as np
from _pyngraph.op import Constant
""" Retrieve Constant inner data.
"""Retrieve Constant inner data.
Internally uses PyBind11 Numpy's buffer protocol.

384
ngraph/python/src/ngraph/opset1/ops.py
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17
ngraph/python/src/ngraph/opset2/ops.py
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@ -14,7 +14,7 @@
# limitations under the License.
# ******************************************************************************
"""! Factory functions for all ngraph ops."""
"""Factory functions for all ngraph ops."""
from typing import Callable, Iterable, List, Optional, Set, Union
import numpy as np
@ -66,7 +66,7 @@ def batch_to_space(
crops_end: NodeInput,
name: Optional[str] = None,
) -> Node:
"""! Perform BatchToSpace operation on the input tensor.
"""Perform BatchToSpace operation on the input tensor.
BatchToSpace permutes data from the batch dimension of the data tensor into spatial dimensions.
@ -84,14 +84,13 @@ def batch_to_space(
@unary_op
def gelu(node: NodeInput, name: Optional[str] = None) -> Node:
r"""! Perform Gaussian Error Linear Unit operation element-wise on data from input node.
r"""Perform Gaussian Error Linear Unit operation element-wise on data from input node.
Computes GELU function:
\f[ f(x) = 0.5\cdot x\cdot(1 + erf( \dfrac{x}{\sqrt{2}}) \f]
For more information refer to:
`Gaussian Error Linear Unit (GELU) <https://arxiv.org/pdf/1606.08415.pdf>`_
For more information refer to [Gaussian Error Linear Unit (GELU)](https://arxiv.org/pdf/1606.08415.pdf>)
@param node: Input tensor. One of: input node, array or scalar.
@param name: Optional output node name.
@ -108,7 +107,7 @@ def mvn(
eps: float = 1e-9,
name: str = None,
) -> Node:
r"""! Perform Mean Variance Normalization operation on data from input node.
r"""Perform Mean Variance Normalization operation on data from input node.
Computes MVN on the input tensor `data` (called `X`) using formula:
@ -131,7 +130,7 @@ def mvn(
@nameable_op
def reorg_yolo(input: Node, stride: List[int], name: Optional[str] = None) -> Node:
"""! Return a node which produces the ReorgYolo operation.
"""Return a node which produces the ReorgYolo operation.
@param input: Input data
@param stride: Stride to reorganize input by
@ -150,7 +149,7 @@ def roi_pooling(
method: str,
name: Optional[str] = None,
) -> Node:
"""! Return a node which produces an ROIPooling operation.
"""Return a node which produces an ROIPooling operation.
@param input: Input feature map {N, C, ...}
@param coords: Coordinates of bounding boxes
@ -175,7 +174,7 @@ def space_to_batch(
pads_end: NodeInput,
name: Optional[str] = None,
) -> Node:
"""! Perform SpaceToBatch operation on the input tensor.
"""Perform SpaceToBatch operation on the input tensor.
SpaceToBatch permutes data tensor blocks of spatial data into batch dimension.
The operator returns a copy of the input tensor where values from spatial blocks dimensions

76
ngraph/python/src/ngraph/opset3/ops.py
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@ -14,7 +14,7 @@
# limitations under the License.
# ******************************************************************************
"""! Factory functions for all ngraph ops."""
"""Factory functions for all ngraph ops."""
from typing import Callable, Iterable, List, Optional, Set, Union
import numpy as np
@ -60,7 +60,7 @@ _get_node_factory_opset3 = partial(_get_node_factory, "opset3")
@nameable_op
def assign(new_value: NodeInput, variable_id: str, name: Optional[str] = None) -> Node:
"""! Return a node which produces the Assign operation.
"""Return a node which produces the Assign operation.
@param new_value: Node producing a value to be assigned to a variable.
@param variable_id: Id of a variable to be updated.
@ -82,7 +82,7 @@ def broadcast(
broadcast_spec: str = "NUMPY",
name: Optional[str] = None,
) -> Node:
"""! Create a node which broadcasts the input node's values along specified axes to a desired shape.
"""Create a node which broadcasts the input node's values along specified axes to a desired shape.
@param data: The node with input tensor data.
@param target_shape: The node with a new shape we want to broadcast tensor to.
@ -109,7 +109,7 @@ def bucketize(
with_right_bound: bool = True,
name: Optional[str] = None,
) -> Node:
"""! Return a node which produces the Bucketize operation.
"""Return a node which produces the Bucketize operation.
@param data: Input data to bucketize
@param buckets: 1-D of sorted unique boundaries for buckets
@ -134,7 +134,7 @@ def cum_sum(
reverse: bool = False,
name: Optional[str] = None,
) -> Node:
"""! Construct a cumulative summation operation.
"""Construct a cumulative summation operation.
@param arg: The tensor to be summed.
@param axis: zero dimension tensor specifying axis position along which sum will be performed.
@ -156,7 +156,7 @@ def embedding_bag_offsets_sum(
per_sample_weights: Optional[NodeInput] = None,
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs sums of bags of embeddings without the intermediate embeddings.
"""Return a node which performs sums of bags of embeddings without the intermediate embeddings.
@param emb_table: Tensor containing the embedding lookup table.
@param indices: Tensor with indices.
@ -183,7 +183,7 @@ def embedding_bag_packed_sum(
per_sample_weights: Optional[NodeInput] = None,
name: Optional[str] = None,
) -> Node:
"""! Return an EmbeddingBagPackedSum node.
"""Return an EmbeddingBagPackedSum node.
EmbeddingSegmentsSum constructs an output tensor by replacing every index in a given
input tensor with a row (from the weights matrix) at that index
@ -211,7 +211,7 @@ def embedding_segments_sum(
per_sample_weights: Optional[NodeInput] = None,
name: Optional[str] = None,
) -> Node:
"""! Return an EmbeddingSegmentsSum node.
"""Return an EmbeddingSegmentsSum node.
EmbeddingSegmentsSum constructs an output tensor by replacing every index in a given
input tensor with a row (from the weights matrix) at that index
@ -248,7 +248,7 @@ def extract_image_patches(
auto_pad: str,
name: Optional[str] = None,
) -> Node:
"""! Return a node which produces the ExtractImagePatches operation.
"""Return a node which produces the ExtractImagePatches operation.
@param image: 4-D Input data to extract image patches.
@param sizes: Patch size in the format of [size_rows, size_cols].
@ -280,7 +280,7 @@ def gru_cell(
linear_before_reset: bool = False,
name: Optional[str] = None,
) -> Node:
"""! Perform GRUCell operation on the tensor from input node.
"""Perform GRUCell operation on the tensor from input node.
GRUCell represents a single GRU Cell that computes the output
using the formula described in the paper: https://arxiv.org/abs/1406.1078
@ -342,7 +342,7 @@ def non_max_suppression(
output_type: str = "i64",
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs NonMaxSuppression.
"""Return a node which performs NonMaxSuppression.
@param boxes: Tensor with box coordinates.
@param scores: Tensor with box scores.
@ -375,7 +375,7 @@ def non_max_suppression(
@nameable_op
def non_zero(data: NodeInput, output_type: str = "i64", name: Optional[str] = None,) -> Node:
"""! Return the indices of the elements that are non-zero.
"""Return the indices of the elements that are non-zero.
@param data: Input data.
@param output_type: Output tensor type.
@ -391,7 +391,7 @@ def non_zero(data: NodeInput, output_type: str = "i64", name: Optional[str] = No
@nameable_op
def read_value(init_value: NodeInput, variable_id: str, name: Optional[str] = None) -> Node:
"""! Return a node which produces the Assign operation.
"""Return a node which produces the Assign operation.
@param init_value: Node producing a value to be returned instead of an unassigned variable.
@param variable_id: Id of a variable to be read.
@ -419,7 +419,7 @@ def rnn_cell(
clip: float = 0.0,
name: Optional[str] = None,
) -> Node:
"""! Perform RNNCell operation on tensor from input node.
"""Perform RNNCell operation on tensor from input node.
It follows notation and equations defined as in ONNX standard:
https://github.com/onnx/onnx/blob/master/docs/Operators.md#RNN
@ -475,7 +475,7 @@ def roi_align(
mode: str,
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs ROIAlign.
"""Return a node which performs ROIAlign.
@param data: Input data.
@param rois: RoIs (Regions of Interest) to pool over.
@ -509,23 +509,23 @@ def scatter_elements_update(
axis: NodeInput,
name: Optional[str] = None,
) -> Node:
"""! Return a node which produces a ScatterElementsUpdate operation.
"""Return a node which produces a ScatterElementsUpdate operation.
@param data: The input tensor to be updated.
@param indices: The tensor with indexes which will be updated.
@param updates: The tensor with update values.
@param axis: The axis for scatter.
@return ScatterElementsUpdate node
ScatterElementsUpdate creates a copy of the first input tensor with updated elements
specified with second and third input tensors.
For each entry in `updates`, the target index in `data` is obtained by combining
the corresponding entry in `indices` with the index of the entry itself: the
index-value for dimension equal to `axis` is obtained from the value of the
corresponding entry in `indices` and the index-value for dimension not equal
to `axis` is obtained from the index of the entry itself.
@param data: The input tensor to be updated.
@param indices: The tensor with indexes which will be updated.
@param updates: The tensor with update values.
@param axis: The axis for scatter.
@return ScatterElementsUpdate node
"""
return _get_node_factory_opset3().create(
"ScatterElementsUpdate", as_nodes(data, indices, updates, axis)
@ -536,7 +536,7 @@ def scatter_elements_update(
def scatter_update(
data: Node, indices: NodeInput, updates: NodeInput, axis: NodeInput, name: Optional[str] = None
) -> Node:
"""! Return a node which produces a ScatterUpdate operation.
"""Return a node which produces a ScatterUpdate operation.
ScatterUpdate sets new values to slices from data addressed by indices.
@ -554,7 +554,7 @@ def scatter_update(
@nameable_op
def shape_of(data: NodeInput, output_type: str = "i64", name: Optional[str] = None) -> Node:
"""! Return a node which produces a tensor containing the shape of its input data.
"""Return a node which produces a tensor containing the shape of its input data.
@param data: The tensor containing the input data.
@param output_type: Output element type.
@ -569,7 +569,17 @@ def shape_of(data: NodeInput, output_type: str = "i64", name: Optional[str] = No
@nameable_op
def shuffle_channels(data: Node, axis: int, groups: int, name: Optional[str] = None) -> Node:
"""! Perform permutation on data in the channel dimension of the input tensor.
"""Perform permutation on data in the channel dimension of the input tensor.
@param data: The node with input tensor.
@param axis: Channel dimension index in the data tensor.
A negative value means that the index should be calculated
from the back of the input data shape.
@param group: The channel dimension specified by the axis parameter
should be split into this number of groups.
@param name: Optional output node name.
@return The new node performing a permutation on data in the channel dimension
of the input tensor.
The operation is the equivalent with the following transformation of the input tensor
`data` of shape [N, C, H, W]:
@ -582,7 +592,7 @@ def shuffle_channels(data: Node, axis: int, groups: int, name: Optional[str] = N
For example:
~~~~~~~~~~~~~{.py}
@code{.py}
Inputs: tensor of shape [1, 6, 2, 2]
data = [[[[ 0., 1.], [ 2., 3.]],
@ -603,17 +613,7 @@ def shuffle_channels(data: Node, axis: int, groups: int, name: Optional[str] = N
[[ 4., 5.], [ 6., 7.]],
[[12., 13.], [14., 15.]],
[[20., 21.], [22., 23.]]]]
~~~~~~~~~~~~~
@param data: The node with input tensor.
@param axis: Channel dimension index in the data tensor.
A negative value means that the index should be calculated
from the back of the input data shape.
@param group: The channel dimension specified by the axis parameter
should be split into this number of groups.
@param name: Optional output node name.
@return The new node performing a permutation on data in the channel dimension
of the input tensor.
@endcode
"""
return _get_node_factory_opset3().create(
"ShuffleChannels", [as_node(data)], {"axis": axis, "groups": groups}
@ -630,7 +630,7 @@ def topk(
index_element_type: str = "i32",
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs TopK.
"""Return a node which performs TopK.
@param data: Input data.
@param k: K.

33
ngraph/python/src/ngraph/opset4/ops.py
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@ -14,7 +14,7 @@
# limitations under the License.
# ******************************************************************************
"""! Factory functions for all ngraph ops."""
"""Factory functions for all ngraph ops."""
from typing import Callable, Iterable, List, Optional, Set, Union
import numpy as np
@ -70,7 +70,7 @@ def ctc_loss(
unique: bool = False,
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs CTCLoss.
"""Return a node which performs CTCLoss.
@param logits: 3-D tensor of logits.
@param logit_length: 1-D tensor of lengths for each object from a batch.
@ -108,7 +108,7 @@ def non_max_suppression(
output_type: str = "i64",
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs NonMaxSuppression.
"""Return a node which performs NonMaxSuppression.
@param boxes: Tensor with box coordinates.
@param scores: Tensor with box scores.
@ -141,7 +141,7 @@ def non_max_suppression(
@nameable_op
def softplus(data: NodeInput, name: Optional[str] = None) -> Node:
"""! Apply SoftPlus operation on each element of input tensor.
"""Apply SoftPlus operation on each element of input tensor.
@param data: The tensor providing input data.
@return The new node with SoftPlus operation applied on each element.
@ -151,7 +151,7 @@ def softplus(data: NodeInput, name: Optional[str] = None) -> Node:
@nameable_op
def mish(data: NodeInput, name: Optional[str] = None,) -> Node:
"""! Return a node which performs Mish.
"""Return a node which performs Mish.
@param data: Tensor with input data floating point type.
@return The new node which performs Mish
@ -161,7 +161,7 @@ def mish(data: NodeInput, name: Optional[str] = None,) -> Node:
@nameable_op
def hswish(data: NodeInput, name: Optional[str] = None,) -> Node:
"""! Return a node which performs HSwish (hard version of Swish).
"""Return a node which performs HSwish (hard version of Swish).
@param data: Tensor with input data floating point type.
@return The new node which performs HSwish
@ -175,7 +175,7 @@ def swish(
beta: Optional[NodeInput] = None,
name: Optional[str] = None,
) -> Node:
"""! Return a node which performing Swish activation function Swish(x, beta=1.0) = x * sigmoid(x * beta)).
"""Return a node which performing Swish activation function Swish(x, beta=1.0) = x * sigmoid(x * beta)).
@param data: Tensor with input data floating point type.
@return The new node which performs Swish
@ -187,7 +187,7 @@ def swish(
@nameable_op
def acosh(node: NodeInput, name: Optional[str] = None) -> Node:
"""! Apply hyperbolic inverse cosine function on the input node element-wise.
"""Apply hyperbolic inverse cosine function on the input node element-wise.
@param node: One of: input node, array or scalar.
@param name: Optional new name for output node.
@ -198,7 +198,7 @@ def acosh(node: NodeInput, name: Optional[str] = None) -> Node:
@nameable_op
def asinh(node: NodeInput, name: Optional[str] = None) -> Node:
"""! Apply hyperbolic inverse sinus function on the input node element-wise.
"""Apply hyperbolic inverse sinus function on the input node element-wise.
@param node: One of: input node, array or scalar.
@param name: Optional new name for output node.
@ -209,7 +209,7 @@ def asinh(node: NodeInput, name: Optional[str] = None) -> Node:
@nameable_op
def atanh(node: NodeInput, name: Optional[str] = None) -> Node:
"""! Apply hyperbolic inverse tangent function on the input node element-wise.
"""Apply hyperbolic inverse tangent function on the input node element-wise.
@param node: One of: input node, array or scalar.
@param name: Optional new name for output node.
@ -226,7 +226,7 @@ def proposal(
attrs: dict,
name: Optional[str] = None,
) -> Node:
"""! Filter bounding boxes and outputs only those with the highest prediction confidence.
"""Filter bounding boxes and outputs only those with the highest prediction confidence.
@param class_probs: 4D input floating point tensor with class prediction scores.
@param bbox_deltas: 4D input floating point tensor with corrected predictions of bounding boxes
@ -295,8 +295,9 @@ def proposal(
Object Detection API models
Default value: "" (empty string)
Required: no
Example of attribute dictionary:
~~~~~~~~~~~~~~~~~~~~~~~~{.py}
@code{.py}
# just required ones
attrs = {
'base_size': 85,
@ -308,7 +309,7 @@ def proposal(
'ratio': [0.1, 1.5, 2.0, 2.5],
'scale': [2, 3, 3, 4],
}
~~~~~~~~~~~~~~~~~~~~~~~~
@endcode
Optional attributes which are absent from dictionary will be set with corresponding default.
@return Node representing Proposal operation.
"""
@ -340,7 +341,7 @@ def proposal(
def reduce_l1(
node: NodeInput, reduction_axes: NodeInput, keep_dims: bool = False, name: Optional[str] = None
) -> Node:
"""! L1-reduction operation on input tensor, eliminating the specified reduction axes.
"""L1-reduction operation on input tensor, eliminating the specified reduction axes.
@param node: The tensor we want to mean-reduce.
@param reduction_axes: The axes to eliminate through mean operation.
@ -357,7 +358,7 @@ def reduce_l1(
def reduce_l2(
node: NodeInput, reduction_axes: NodeInput, keep_dims: bool = False, name: Optional[str] = None
) -> Node:
"""! L2-reduction operation on input tensor, eliminating the specified reduction axes.
"""L2-reduction operation on input tensor, eliminating the specified reduction axes.
@param node: The tensor we want to mean-reduce.
@param reduction_axes: The axes to eliminate through mean operation.
@ -385,7 +386,7 @@ def lstm_cell(
clip: float = 0.0,
name: Optional[str] = None,
) -> Node:
"""! Return a node which performs LSTMCell operation.
"""Return a node which performs LSTMCell operation.
@param X: The input tensor with shape: [batch_size, input_size].
@param initial_hidden_state: The hidden state tensor with shape: [batch_size, hidden_size].

2
ngraph/python/src/ngraph/opset_utils.py
View File

@ -27,7 +27,7 @@ from ngraph.utils.types import (
def _get_node_factory(opset_version: Optional[str] = None) -> NodeFactory:
"""! Return NodeFactory configured to create operators from specified opset version."""
"""Return NodeFactory configured to create operators from specified opset version."""
if opset_version:
return NodeFactory(opset_version)
else:

2
ngraph/python/src/ngraph/utils/__init__.py
View File

@ -13,4 +13,4 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
"""! Generic utilities. Factor related functions out to separate files."""
"""Generic utilities. Factor related functions out to separate files."""

2
ngraph/python/src/ngraph/utils/broadcasting.py
View File

@ -26,7 +26,7 @@ log = logging.getLogger(__name__)
def get_broadcast_axes(
output_shape: TensorShape, input_shape: TensorShape, axis: int = None
) -> AxisSet:
"""! Generate a list of broadcast axes for ngraph++ broadcast.
"""Generate a list of broadcast axes for ngraph++ broadcast.
Informally, a broadcast "adds" axes to the input tensor,
replicating elements from the input tensor as needed to fill the new dimensions.

6
ngraph/python/src/ngraph/utils/decorators.py
View File

@ -27,7 +27,7 @@ def _set_node_friendly_name(node: Node, **kwargs: Any) -> Node:
def nameable_op(node_factory_function: Callable) -> Callable:
"""! Set the name to the ngraph operator returned by the wrapped function."""
"""Set the name to the ngraph operator returned by the wrapped function."""
@wraps(node_factory_function)
def wrapper(*args: Any, **kwargs: Any) -> Node:
@ -39,7 +39,7 @@ def nameable_op(node_factory_function: Callable) -> Callable:
def unary_op(node_factory_function: Callable) -> Callable:
"""! Convert the first input value to a Constant Node if a numeric value is detected."""
"""Convert the first input value to a Constant Node if a numeric value is detected."""
@wraps(node_factory_function)
def wrapper(input_value: NodeInput, *args: Any, **kwargs: Any) -> Node:
@ -52,7 +52,7 @@ def unary_op(node_factory_function: Callable) -> Callable:
def binary_op(node_factory_function: Callable) -> Callable:
"""! Convert the first two input values to Constant Nodes if numeric values are detected."""
"""Convert the first two input values to Constant Nodes if numeric values are detected."""
@wraps(node_factory_function)
def wrapper(left: NodeInput, right: NodeInput, *args: Any, **kwargs: Any) -> Node:

14
ngraph/python/src/ngraph/utils/input_validation.py
View File

@ -14,7 +14,7 @@
# limitations under the License.
# ******************************************************************************
"""! Helper functions for validating user input."""
"""Helper functions for validating user input."""
import logging
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Type
@ -27,7 +27,7 @@ log = logging.getLogger(__name__)
def assert_list_of_ints(value_list: Iterable[int], message: str) -> None:
"""! Verify that the provided value is an iterable of integers."""
"""Verify that the provided value is an iterable of integers."""
try:
for value in value_list:
if not isinstance(value, int):
@ -39,7 +39,7 @@ def assert_list_of_ints(value_list: Iterable[int], message: str) -> None:
def _check_value(op_name, attr_key, value, val_type, cond=None):
# type: (str, str, Any, Type, Optional[Callable[[Any], bool]]) -> bool
"""! Check whether provided value satisfies specified criteria.
"""Check whether provided value satisfies specified criteria.
@param op_name: The operator name which attributes are checked.
@param attr_key: The attribute name.
@ -67,7 +67,7 @@ def _check_value(op_name, attr_key, value, val_type, cond=None):
def check_valid_attribute(op_name, attr_dict, attr_key, val_type, cond=None, required=False):
# type: (str, dict, str, Type, Optional[Callable[[Any], bool]], Optional[bool]) -> bool
"""! Check whether specified attribute satisfies given criteria.
"""Check whether specified attribute satisfies given criteria.
@param op_name: The operator name which attributes are checked.
@param attr_dict: Dictionary containing key-value attributes to check.
@ -110,7 +110,7 @@ def check_valid_attributes(
requirements, # type: List[Tuple[str, bool, Type, Optional[Callable]]]
):
# type: (...) -> bool
"""! Perform attributes validation according to specified type, value criteria.
"""Perform attributes validation according to specified type, value criteria.
@param op_name: The operator name which attributes are checked.
@param attributes: The dictionary with user provided attributes to check.
@ -130,7 +130,7 @@ def check_valid_attributes(
def is_positive_value(x): # type: (Any) -> bool
"""! Determine whether the specified x is positive value.
"""Determine whether the specified x is positive value.
@param x: The value to check.
@ -140,7 +140,7 @@ def is_positive_value(x): # type: (Any) -> bool
def is_non_negative_value(x): # type: (Any) -> bool
"""! Determine whether the specified x is non-negative value.
"""Determine whether the specified x is non-negative value.
@param x: The value to check.

16
ngraph/python/src/ngraph/utils/node_factory.py
View File

@ -9,10 +9,10 @@ DEFAULT_OPSET = "opset6"
class NodeFactory(object):
"""! Factory front-end to create node objects."""
"""Factory front-end to create node objects."""
def __init__(self, opset_version: str = DEFAULT_OPSET) -> None:
"""! Create the NodeFactory object.
"""Create the NodeFactory object.
@param opset_version: The opset version the factory will use to produce ops from.
"""
@ -24,7 +24,7 @@ class NodeFactory(object):
arguments: List[Union[Node, Output]],
attributes: Optional[Dict[str, Any]] = None,
) -> Node:
"""! Create node object from provided description.
"""Create node object from provided description.
The user does not have to provide all node's attributes, but only required ones.
@ -84,7 +84,7 @@ class NodeFactory(object):
@staticmethod
def _normalize_attr_name(attr_name: str, prefix: str) -> str:
"""! Normalize attribute name.
"""Normalize attribute name.
@param attr_name: The attribute name.
@param prefix: The prefix to attach to attribute name.
@ -98,7 +98,7 @@ class NodeFactory(object):
@classmethod
def _normalize_attr_name_getter(cls, attr_name: str) -> str:
"""! Normalize atr name to be suitable for getter function name.
"""Normalize atr name to be suitable for getter function name.
@param attr_name: The attribute name to normalize
@ -108,7 +108,7 @@ class NodeFactory(object):
@classmethod
def _normalize_attr_name_setter(cls, attr_name: str) -> str:
"""! Normalize attribute name to be suitable for setter function name.
"""Normalize attribute name to be suitable for setter function name.
@param attr_name: The attribute name to normalize
@ -118,7 +118,7 @@ class NodeFactory(object):
@staticmethod
def _get_node_attr_value(node: Node, attr_name: str) -> Any:
"""! Get provided node attribute value.
"""Get provided node attribute value.
@param node: The node we retrieve attribute value from.
@param attr_name: The attribute name.
@ -132,7 +132,7 @@ class NodeFactory(object):
@staticmethod
def _set_node_attr_value(node: Node, attr_name: str, value: Any) -> None:
"""! Set the node attribute value.
"""Set the node attribute value.
@param node: The node we change attribute value for.
@param attr_name: The attribute name.

2
ngraph/python/src/ngraph/utils/reduction.py
View File

@ -20,7 +20,7 @@ from ngraph.impl import Node
def get_reduction_axes(node: Node, reduction_axes: Optional[Iterable[int]]) -> Iterable[int]:
"""! Get reduction axes if it is None and convert it to set if its type is different.
"""Get reduction axes if it is None and convert it to set if its type is different.
If reduction_axes is None we default to reduce all axes.

32
ngraph/python/src/ngraph/utils/tensor_iterator_types.py
View File

@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
"""! Helper classes for aggregating TensorIterator input/output desciptor attributes."""
"""Helper classes for aggregating TensorIterator input/output desciptor attributes."""
from typing import List
@ -22,14 +22,14 @@ from ngraph.impl.op import Parameter
class GraphBody(object):
"""! Class containing graph parameters and results."""
"""Class containing graph parameters and results."""
def __init__(self, parameters: List[Parameter], results: List[Node],) -> None:
self.parameters = parameters
self.results = results
def serialize(self) -> dict:
"""! Serialize GraphBody as a dictionary."""
"""Serialize GraphBody as a dictionary."""
return {
"parameters": self.parameters,
"results": self.results,
@ -37,14 +37,14 @@ class GraphBody(object):
class TensorIteratorInputDesc(object):
"""! Represents a generic input descriptor for TensorIterator operator."""
"""Represents a generic input descriptor for TensorIterator operator."""
def __init__(self, input_idx: int, body_parameter_idx: int,) -> None:
self.input_idx = input_idx
self.body_parameter_idx = body_parameter_idx
def serialize(self) -> dict:
"""! Serialize TensorIteratorInputDesc as a dictionary."""
"""Serialize TensorIteratorInputDesc as a dictionary."""
return {
"input_idx": self.input_idx,
"body_parameter_idx": self.body_parameter_idx,
@ -52,7 +52,7 @@ class TensorIteratorInputDesc(object):
class TensorIteratorSliceInputDesc(TensorIteratorInputDesc):
"""! Represents a TensorIterator graph body input formed from slices of TensorIterator input."""
"""Represents a TensorIterator graph body input formed from slices of TensorIterator input."""
def __init__(
self,
@ -72,7 +72,7 @@ class TensorIteratorSliceInputDesc(TensorIteratorInputDesc):
self.axis = axis
def serialize(self) -> dict:
"""! Serialize TensorIteratorSliceInputDesc as a dictionary."""
"""Serialize TensorIteratorSliceInputDesc as a dictionary."""
output = super().serialize()
output["start"] = self.start
output["stride"] = self.stride
@ -83,7 +83,7 @@ class TensorIteratorSliceInputDesc(TensorIteratorInputDesc):
class TensorIteratorMergedInputDesc(TensorIteratorInputDesc):
"""! Represents a TensorIterator graph body input with initial value in the first iteration.
"""Represents a TensorIterator graph body input with initial value in the first iteration.
Later on, this input value is computed inside graph body.
"""
@ -93,28 +93,28 @@ class TensorIteratorMergedInputDesc(TensorIteratorInputDesc):
self.body_value_idx = body_value_idx
def serialize(self) -> dict:
"""! Serialize TensorIteratorMergedInputDesc as a dictionary."""
"""Serialize TensorIteratorMergedInputDesc as a dictionary."""
output = super().serialize()
output["body_value_idx"] = self.body_value_idx
return output
class TensorIteratorInvariantInputDesc(TensorIteratorInputDesc):
"""! Represents a TensorIterator graph body input that has invariant value during iteration."""
"""Represents a TensorIterator graph body input that has invariant value during iteration."""
def __init__(self, input_idx: int, body_parameter_idx: int,) -> None:
super().__init__(input_idx, body_parameter_idx)
class TensorIteratorOutputDesc(object):
"""! Represents a generic output descriptor for TensorIterator operator."""
"""Represents a generic output descriptor for TensorIterator operator."""
def __init__(self, body_value_idx: int, output_idx: int,) -> None:
self.body_value_idx = body_value_idx
self.output_idx = output_idx
def serialize(self) -> dict:
"""! Serialize TensorIteratorOutputDesc as a dictionary."""
"""Serialize TensorIteratorOutputDesc as a dictionary."""
return {
"body_value_idx": self.body_value_idx,
"output_idx": self.output_idx,
@ -122,21 +122,21 @@ class TensorIteratorOutputDesc(object):
class TensorIteratorBodyOutputDesc(TensorIteratorOutputDesc):
"""! Represents an output from a specific iteration."""
"""Represents an output from a specific iteration."""
def __init__(self, body_value_idx: int, output_idx: int, iteration: int,) -> None:
super().__init__(body_value_idx, output_idx)
self.iteration = iteration
def serialize(self) -> dict:
"""! Serialize TensorIteratorBodyOutputDesc as a dictionary."""
"""Serialize TensorIteratorBodyOutputDesc as a dictionary."""
output = super().serialize()
output["iteration"] = self.iteration
return output
class TensorIteratorConcatOutputDesc(TensorIteratorOutputDesc):
"""! Represents an output produced by concatenation of output from each iteration."""
"""Represents an output produced by concatenation of output from each iteration."""
def __init__(
self,
@ -156,7 +156,7 @@ class TensorIteratorConcatOutputDesc(TensorIteratorOutputDesc):
self.axis = axis
def serialize(self) -> dict:
"""! Serialize TensorIteratorConcatOutputDesc as a dictionary."""
"""Serialize TensorIteratorConcatOutputDesc as a dictionary."""
output = super().serialize()
output["start"] = self.start
output["stride"] = self.stride

18
ngraph/python/src/ngraph/utils/types.py
View File

@ -13,7 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
"""! Functions related to converting between Python and numpy types and ngraph types."""
"""Functions related to converting between Python and numpy types and ngraph types."""
import logging
from typing import List, Union
@ -66,7 +66,7 @@ ngraph_to_numpy_types_str_map = [
def get_element_type(data_type: NumericType) -> NgraphType:
"""! Return an ngraph element type for a Python type or numpy.dtype."""
"""Return an ngraph element type for a Python type or numpy.dtype."""
if data_type is int:
log.warning("Converting int type of undefined bitwidth to 32-bit ngraph integer.")
return NgraphType.i32
@ -85,7 +85,7 @@ def get_element_type(data_type: NumericType) -> NgraphType:
def get_element_type_str(data_type: NumericType) -> str:
"""! Return an ngraph element type string representation for a Python type or numpy dtype."""
"""Return an ngraph element type string representation for a Python type or numpy dtype."""
if data_type is int:
log.warning("Converting int type of undefined bitwidth to 32-bit ngraph integer.")
return "i32"
@ -105,7 +105,7 @@ def get_element_type_str(data_type: NumericType) -> str:
def get_dtype(ngraph_type: NgraphType) -> np.dtype:
"""! Return a numpy.dtype for an ngraph element type."""
"""Return a numpy.dtype for an ngraph element type."""
np_type = next(
(np_type for (ng_type, np_type) in ngraph_to_numpy_types_map if ng_type == ngraph_type),
None,
@ -118,14 +118,14 @@ def get_dtype(ngraph_type: NgraphType) -> np.dtype:
def get_ndarray(data: NumericData) -> np.ndarray:
"""! Wrap data into a numpy ndarray."""
"""Wrap data into a numpy ndarray."""
if type(data) == np.ndarray:
return data
return np.array(data)
def get_shape(data: NumericData) -> TensorShape:
"""! Return a shape of NumericData."""
"""Return a shape of NumericData."""
if type(data) == np.ndarray:
return data.shape # type: ignore
elif type(data) == list:
@ -134,7 +134,7 @@ def get_shape(data: NumericData) -> TensorShape:
def make_constant_node(value: NumericData, dtype: NumericType = None) -> Constant:
"""! Return an ngraph Constant node with the specified value."""
"""Return an ngraph Constant node with the specified value."""
ndarray = get_ndarray(value)
if dtype:
element_type = get_element_type(dtype)
@ -145,7 +145,7 @@ def make_constant_node(value: NumericData, dtype: NumericType = None) -> Constan
def as_node(input_value: NodeInput) -> Node:
"""! Return input values as nodes. Scalars will be converted to Constant nodes."""
"""Return input values as nodes. Scalars will be converted to Constant nodes."""
if issubclass(type(input_value), Node):
return input_value
if issubclass(type(input_value), Output):
@ -154,5 +154,5 @@ def as_node(input_value: NodeInput) -> Node:
def as_nodes(*input_values: NodeInput) -> List[Node]:
"""! Return input values as nodes. Scalars will be converted to Constant nodes."""
"""Return input values as nodes. Scalars will be converted to Constant nodes."""
return [as_node(input_value) for input_value in input_values]