diff --git a/LICENSE b/LICENSE
new file mode 100644
index 000000000..e77bd090e
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,203 @@
+Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
+
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+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+   Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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diff --git a/README.md b/README.md
new file mode 100644
index 000000000..e479d81c2
--- /dev/null
+++ b/README.md
@@ -0,0 +1,46 @@
+### WORK-IN-PROGRESS
+
+# PaddlePaddle to ONNX model convertor
+
+Converts a PaddlePaddle model (`ProgramDesc` + parameters) into an ONNX graph. Uses the ONNX pip library and target PaddlePaddle **Fluid**.
+
+To understand PaddlePaddle's (non-)graph way of representing a deep learning program, a `ProgramDesc`, refer to: https://github.com/PaddlePaddle/Paddle/blob/develop/doc/fluid/design/concepts/program.md.
+
+## Status
+
+Targets Paddle->ONNX conversion for now, and will consequently support the reverse too.
+
+Currently a work-in-progress tool since there a features in PaddlePaddle not supported in ONNX today and vice-versa.
+
+## Usage
+
+First, generate model directory by running any fluid test / example and write the model using the `fluid.io.save_inference_model` API.
+
+Then, run `convert.py` by providing the generated model directory to the argument `---modeldir`.
+
+
+## Installation
+
+(TBD)
+
+Create a virtual environment and install ONNX using PIP.
+```
+pip install onnx==1.1
+```
+
+Build PaddlePaddle's `develop` branch from source using info here:
+http://paddlepaddle.org/docs/develop/documentation/en/build_and_install/build_from_source_en.html
+
+## Testing
+
+TBD
+
+## Supported models
+
+We aim to at least support all the models from our model bank. During our preliminary stage, we plan to support the models generated from:
+
+- [fit_a_line](https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/fluid/tests/book/test_fit_a_line.py)
+- [fit_a_line](https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/fluid/tests/book/test_fit_a_line.py)
+
+## License
+Provided under the [Apache-2.0 license](LICENSE).
diff --git a/convert.py b/convert.py
new file mode 100644
index 000000000..d6e3451cf
--- /dev/null
+++ b/convert.py
@@ -0,0 +1,29 @@
+import argparse
+
+from onnx import *
+import paddle.fluid as fluid
+
+# import ops
+
+def convert(dirname=''):
+    # Read the model files.
+    # place = fluid.CPUPlace()
+    # exe = fluid.Executor(place)
+
+    # inference_scope = fluid.core.Scope()
+    # with fluid.scope_guard(inference_scope):
+    #   [inference_program, feed_target_names,
+    #       fetch_targets] = fluid.io.load_inference_model(dirname, exe)
+
+    # Using blocks in programs, create nodes using:
+    # helper.make_program
+    # helper.make_node
+    # ops.PADDLE_TO_ONNX
+
+
+if __name__ == "__main__":
+    # Read arguments: path to model.
+    # parser = argparse.ArgumentParser()
+    # parser.add_argument("--modeldir", required=True, help="input model")
+
+    convert()
diff --git a/ops.py b/ops.py
new file mode 100644
index 000000000..b29ef16aa
--- /dev/null
+++ b/ops.py
@@ -0,0 +1,548 @@
+"""
+Priority of ops (uniques) to figure out support for.
+
+test_fit_a_line.py
+- mean
+- mul
+- elementwise_add
+- elementwise_sub
+- fill_constant
+
+^ Try to make this run before proceeding.
+
+test_machine_translation.py
+- lookup_table
+- tanh
+- lstm
+- sequence_pool
+- lookup_table
+- lod_rank_table
+- max_sequence_len
+- less_than
+- lod_tensor_to_array
+- write_to_array
+- while
+- array_to_lod_tensor
+- cross_entropy
+- lod_tensor_to_array
+- read_from_array
+- sum
+- scale
+- adagrad
+- shrink_rnn_memory
+- softmax
+- write_to_array
+- increment
+"""
+
+# Based on the ONNX 1.0 operator list generated on March 26th, 2018.
+# Reference for paddle operator availability taken from:
+#     https://github.com/PaddlePaddle/Paddle/issues/8028
+
+# ONNX Ops that use multiple Paddle ops are keyed by '<op1>,<op2>' fed into the
+# modifier.
+
+PADDLE_TO_ONNX = {
+    # Paddle op name : (ONNX op name, modifier)
+    'abs': ('Abs', abs_op),
+    'elementwise_add': ('Add', add_op),
+
+    # '': 'And', # ?
+    # 'ArgMax', NEEDS ATTENTION.
+    # 'ArgMin', NEEDS ATTENTION.
+    '': ('AveragePool', averagepool_op),
+    'batch_norm': ('BatchNormalization', batchnorm_op),
+    'cast': ('Cast', cast_op),
+    # 'Ceil', NEEDS ATTENTION.
+    'cast': ('Clip', clip_op),
+    'concat': ('Concat', concat_op),
+
+    ',': ('Constant', constant_op),
+    'conv': ('Conv', conv_op),
+
+    # Need to continue the mapping below.
+    'ConvTranspose',
+    'DepthToSpace',
+    'Div',
+    'Dropout',
+    'Elu',
+    'Equal',
+    'Exp',
+    'Flatten',
+    # 'Floor', NEEDS ATTENTION.
+    'GRU',
+    'Gather',
+    'Gemm',
+    'GlobalAveragePool',
+    'GlobalLpPool',
+    'GlobalMaxPool',
+    'Greater',
+    'HardSigmoid',
+    # 'Hardmax', NEEDS ATTENTION.
+    # 'InstanceNormalization', NEEDS ATTENTION.
+    'LRN',
+    'LSTM',
+    'LeakyRelu',
+    'Less',
+    'Log',
+    ',': 'LogSoftmax',
+    'LpNormalization',
+    'LpPool',
+    'MatMul',
+    'Max',
+    # 'MaxPool', NEEDS ATTENTION.
+    'MaxRoiPool',
+    'mean': ('Mean', mean_op),
+    'Min',
+    'mul': ('Mul', mul_op),
+    ',': 'Neg',
+    'Not',
+    'Or',
+    'PRelu',
+    'Pad',
+    'Pow',
+    ',': 'RNN',
+    'RandomNormal',
+    # 'RandomNormalLike', NEEDS ATTENTION.
+    # 'RandomUniform', NEEDS ATTENTION.
+    # 'RandomUniformLike', NEEDS ATTENTION.
+    'Reciprocal',
+    'ReduceL1',
+    'ReduceL2',
+    ',': 'ReduceLogSum',
+    ',': 'ReduceLogSumExp',
+    'ReduceMax',
+    'ReduceMean',
+    'ReduceMin',
+    # 'ReduceProd', NEEDS ATTENTION.
+    'ReduceSum',
+    ',': 'ReduceSumSquare',
+    'Relu',
+    'Reshape',
+    # 'Selu', NEEDS ATTENTION.
+    'Shape',
+    'Sigmoid',
+    'Size',
+    # 'Slice', NEEDS ATTENTION.
+    'Softmax',
+    'Softplus',
+    'Softsign',
+    'SpaceToDepth',
+    'Split',
+    'Sqrt',
+    # 'Squeeze', NEEDS ATTENTION.
+    'elementwise_sub': ('Sub', sub_op),
+    'Sum',
+    'Tanh',
+    'Tile',
+    'TopK',
+    'Transpose',
+    # 'Unsqueeze', NEEDS ATTENTION.
+    'Xor',
+    # 'experimental ATen'
+    # ',': 'experimental Affine'
+    # 'experimental ConstantFill'
+    # 'experimental Crop'
+    # 'experimental FC'
+    # 'experimental GRUUnit'
+    # 'experimental GivenTensorFill'
+    # 'assign': 'experimental Identity'
+    # 'experimental If'
+    # ',': 'experimental ImageScaler'
+    # 'experimental Loop'
+    # 'experimental LoopIndexTensor'
+    # 'experimental MeanVarianceNormalization'
+    # 'experimental ParametricSoftplus'
+    # 'experimental Scale'
+    # 'experimental ScaledTanh'
+    # 'experimental ThresholdedRelu'
+    # 'experimental Upsample'
+}
+
+def abs_op():
+    pass
+
+
+def add_op():
+    pass
+
+
+def and_op():
+    """
+    Need to support broadcast.
+    """
+    pass
+
+
+def argmax_op():
+    pass
+
+
+def argmin_op():
+    pass
+
+
+def averagepool_op():
+    """
+    Need to support more pad mode.
+    """
+    pass
+
+
+def batchnorm_op():
+    pass
+
+
+def cast_op():
+    pass
+
+
+def ceil_op():
+    pass
+
+
+def clip_op():
+    pass
+
+
+def concat_op():
+    pass
+
+
+def constant_op():
+    pass
+
+
+def conv_op():
+    """
+    Need to support broadcast.
+    """
+    pass
+
+
+def convtranspose_op():
+    pass
+
+
+def depthtospace_op():
+    pass
+
+
+def div_op():
+    pass
+
+
+def dropout_op():
+    pass
+
+
+def elu_op():
+    pass
+
+
+def equal_op():
+    pass
+
+
+def dropout_op():
+    pass
+
+
+def exp_op():
+    pass
+
+
+def flatten_op():
+    pass
+
+
+def floor_op():
+    pass
+
+
+def gru_op():
+    pass
+
+
+def gather_op():
+    pass
+
+
+def gemm_op():
+    pass
+
+
+def globalaveragepool_op():
+    pass
+
+
+def globallppool_op():
+    pass
+
+
+def globalmaxpool_op():
+    pass
+
+
+def greater_op():
+    pass
+
+
+def hardsigmoid_op():
+    pass
+
+
+def hardmax_op():
+    pass
+
+
+def instancenormalization_op():
+    pass
+
+
+def lrn_op():
+    pass
+
+
+def lstm_op():
+    pass
+
+
+def leakyrelu_op():
+    pass
+
+
+def less_op():
+    pass
+
+
+def log_op():
+    pass
+
+
+def logsoftmax_op():
+    pass
+
+
+def lpnormalization_op():
+    pass
+
+
+def lppool_op():
+    pass
+
+
+def matmul_op():
+    pass
+
+
+def max_op():
+    pass
+
+
+def maxpool_op():
+    """
+    Need to support broadcast.
+    """
+    pass
+
+
+def maxroipool_op():
+    pass
+
+
+def mean_op():
+    pass
+
+
+def min_op():
+    pass
+
+
+def mul_op():
+    pass
+
+
+def neg_op():
+    pass
+
+
+def not_op():
+    """
+    Need to support broadcast.
+    """
+    pass
+
+
+def or_op():
+    """
+    Need to support broadcast.
+    """
+    pass
+
+
+def prelu_op():
+    pass
+
+
+def pad_op():
+    pass
+
+
+def pow_op():
+    pass
+
+
+def rnn_op():
+    pass
+
+
+def randomnormal_op():
+    pass
+
+
+def randomnormallike_op():
+    pass
+
+
+def randomuniform_op():
+    pass
+
+
+def randomuniformlike_op():
+    pass
+
+
+def reciprocal_op():
+    pass
+
+
+def reducel1_op():
+    pass
+
+
+def reducel2_op():
+    pass
+
+
+def reducelogsum_op():
+    pass
+
+
+def reducelogsumexp_op():
+    pass
+
+
+def reducemax_op():
+    pass
+
+
+def reducemean_op():
+    pass
+
+
+def reducemin_op():
+    pass
+
+
+def reduceprod_op():
+    pass
+
+
+def reducesum_op():
+    pass
+
+
+def reducesumsquare_op():
+    pass
+
+
+def relu_op():
+    pass
+
+
+def reshape_op():
+    pass
+
+
+def selu_op():
+    pass
+
+
+def shape_op():
+    pass
+
+
+def sigmoid_op():
+    pass
+
+
+def size_op():
+    pass
+
+
+def slice_op():
+    pass
+
+
+def softmax_op():
+    pass
+
+
+def softplus_op():
+    pass
+
+
+def softsign_op():
+    pass
+
+
+def spacetodepth_op():
+    pass
+
+
+def split_op():
+    pass
+
+
+def sqrt_op():
+    pass
+
+
+def squeeze_op():
+    pass
+
+
+def sub_op():
+    pass
+
+
+def sum_op():
+    pass
+
+
+def tanh_op():
+    pass
+
+
+def tile_op():
+    pass
+
+
+def topk_op():
+    pass
+
+
+def transpose_op():
+    pass
+
+
+def unsqueeze_op():
+    pass
+
+
+def xor_op():
+    """
+    Need to support broadcast.
+    """
+    pass
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/types.py b/types.py
new file mode 100644
index 000000000..459ee9032
--- /dev/null
+++ b/types.py
@@ -0,0 +1,19 @@
+from onnx import onnx_pb2
+import paddle.fluid.core as core
+
+
+PADDLE_TO_ONNX_DTYPE = {
+    core.VarDesc.VarType.FP32: onnx_pb2.TensorProto.FLOAT,
+    core.VarDesc.VarType.FP64: onnx_pb2.TensorProto.FLOAT16,
+    '': onnx_pb2.TensorProto.DOUBLE,
+    core.VarDesc.VarType.INT32: onnx_pb2.TensorProto.INT32,
+    core.VarDesc.VarType.INT16: onnx_pb2.TensorProto.INT16,
+    '': onnx_pb2.TensorProto.INT8,
+    '': onnx_pb2.TensorProto.UINT8,
+    core.VarDesc.VarType.INT16: onnx_pb2.TensorProto.UINT16,
+    core.VarDesc.VarType.INT64: onnx_pb2.TensorProto.INT64,
+    '': onnx_pb2.TensorProto.STRING,
+    '': onnx_pb2.TensorProto.COMPLEX64,
+    '': onnx_pb2.TensorProto.COMPLEX128,
+    core.VarDesc.VarType.BOOL: onnx_pb2.TensorProto.BOOL,
+}