LP Extractor Protocol - Revision history

Ed at 17:47, 21 September 2020

2020-09-21T17:47:39Z

2020-09-21T17:34:34Z

2020-09-20T16:29:14Z

2019-05-30T16:26:17Z

DSL Encoder

2019-04-26T22:15:50Z

2019-04-19T21:00:57Z

DFS Encoding

2019-04-18T20:51:34Z

2019-04-18T20:51:13Z

2019-04-18T05:37:07Z

2019-04-06T16:36:16Z

@@ Line 1: / Line 1: @@
 {{Project
-|Has project output=
+|Has project output=Tool
 |Has sponsor=Kauffman Incubator Project
 |Has title=LP Extractor Protocol

@@ Line 1: / Line 1: @@
 {{Project
 |Has sponsor=Kauffman Incubator Project
 |Has title=LP Extractor Protocol

@@ Line 1: / Line 1: @@
 {{Project
 |Has title=LP Extractor Protocol
 |Has owner=Lasya Rajan,

← Older revision		Revision as of 16:26, 30 May 2019
Line 168:		Line 168:

	==DSL Encoder==		==DSL Encoder==
−	To encode the structure of the DSL scripts, we can try using one-hot vector. More details can be found [https://blog.floydhub.com/turning-design-mockups-into-code-with-deep-learning/ here] and [~~http://www.edegan.com/wiki/DSL_Encoding here~~].	+	To encode the structure of the DSL scripts, we can try using one-hot vector. More details can be found [https://blog.floydhub.com/turning-design-mockups-into-code-with-deep-learning/ here] and on the [[DSL Encoding]] page.

← Older revision		Revision as of 22:15, 26 April 2019
Line 166:		Line 166:
	: Here is a visualization of the model that we might want to use for our extractor		: Here is a visualization of the model that we might want to use for our extractor
	[[File: Extractor-Model.png\| first diagram of extractor model]]		[[File: Extractor-Model.png\| first diagram of extractor model]]
		+
		+	==DSL Encoder==
		+	To encode the structure of the DSL scripts, we can try using one-hot vector. More details can be found [https://blog.floydhub.com/turning-design-mockups-into-code-with-deep-learning/ here] and [http://www.edegan.com/wiki/DSL_Encoding here].

@@ Line 133: / Line 133: @@
 : Github repo that contains reference implementation of node2vec algorithm as a python module. See above node2vec paper.
 : A [https://github.com/thunlp/OpenNE toolkit] containing node2vec implemented in a framework based on tensorflow
+: [https://towardsdatascience.com/node2vec-embeddings-for-graph-data-32a866340fef Here] is a very good and elementary introduction to node2vec
 * [https://networkx.github.io/documentation/stable/index.html NetworkX]
 : NetworkX is a Python package for loading, visualizing, and processing graph data. Includes built in functions for DFS encoding, and constructing adjacency and edges to vertices matrices.

@@ Line 164: / Line 164: @@
 === Proposed Model ===
-: Here is a visualization of the model what we might want to use for our extractor
+: Here is a visualization of the model that we might want to use for our extractor
 [[File: Extractor-Model.png| first diagram of extractor model]]

← Older revision		Revision as of 20:51, 18 April 2019
Line 162:		Line 162:
	=== Useful tutorials ===		=== Useful tutorials ===
	: Since we will be using a two-layer LSTMs in tensorflow, this [https://medium.com/@erikhallstrm/using-the-tensorflow-multilayered-lstm-api-f6e7da7bbe40 article] might be useful.		: Since we will be using a two-layer LSTMs in tensorflow, this [https://medium.com/@erikhallstrm/using-the-tensorflow-multilayered-lstm-api-f6e7da7bbe40 article] might be useful.
		+
		+	=== Proposed Model ===
		+	: Here is a visualization of the model what we might want to use for our extractor
		+	[[File: Extractor-Model.png\| first diagram of extractor model]]

← Older revision		Revision as of 05:37, 18 April 2019
Line 159:		Line 159:
	* [https://www.h5py.org/ H5PY]		* [https://www.h5py.org/ H5PY]
	: The h5py package can be used to store large amounts of numerical data, and integrates well with NumPy		: The h5py package can be used to store large amounts of numerical data, and integrates well with NumPy
		+
		+	=== Useful tutorials ===
		+	: Since we will be using a two-layer LSTMs in tensorflow, this [https://medium.com/@erikhallstrm/using-the-tensorflow-multilayered-lstm-api-f6e7da7bbe40 article] might be useful.

@@ Line 142: / Line 142: @@
 * [http://www.numpy.org/ NumPy]
 : NumPy is a computing package that includes a N-dimensional array object (useful in encoding) and many other functions to process data. Is required for pix2code.
 === General ===