#
# Copyright (c) 2021-2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

from collections import OrderedDict

import numpy as np
import onnx_graphsurgeon as gs

# the same model as 08-Tool/OnnxGraphSurgeon/01-CreateModel
tensor0 = gs.Variable("tensor0", np.float32, ["B", 3, 64, 64])
tensor1 = gs.Variable("tensor1", np.float32, ["B", 1, 64, 64])
tensor2 = gs.Variable("tensor2", np.float32, None)
tensor3 = gs.Variable("tensor3", np.float32, None)
constant0 = gs.Constant(name="constant0", values=np.ones(shape=[1, 3, 3, 3], dtype=np.float32))
constant1 = gs.Constant(name="constant1", values=np.ones(shape=[1], dtype=np.float32))
node0 = gs.Node("Conv", "myConv", inputs=[tensor0, constant0], outputs=[tensor1])
node0.attrs = OrderedDict([
    ["dilations", [1, 1]],
    ["kernel_shape", [3, 3]],
    ["pads", [1, 1, 1, 1]],
    ["strides", [1, 1]],
])
node1 = gs.Node("Add", "myAdd", inputs=[tensor1, constant1], outputs=[tensor2])
node2 = gs.Node("Relu", "myRelu", inputs=[tensor2], outputs=[tensor3])
graph = gs.Graph(nodes=[node0, node1, node2], inputs=[tensor0], outputs=[tensor3])

"""
Member of IBuilder:
++++        shown above
----        not shown above
[no prefix] others

Constant
++++Graph
++++Node
OnnxGraphSurgeonException
Tensor
++++Variable
__builtins__
__cached__
__doc__
__file__
__loader__
__name__
__package__
__path__
__spec__
__version__
export_onnx
exporters
import_onnx
importers
ir
logger
util']
"""
