Data Flow Graph (DFG) - Revision history

BPeat: Text replacement - "http:" to "https:"

2023-03-28T12:41:16Z

Text replacement - "http:" to "https:"

BPeat at 14:40, 3 March 2019

2019-03-03T14:40:58Z

BPeat at 02:51, 23 February 2019

2019-02-23T02:51:28Z

BPeat at 02:43, 23 February 2019

2019-02-23T02:43:59Z

BPeat at 02:38, 23 February 2019

2019-02-23T02:38:41Z

BPeat at 02:32, 23 February 2019

2019-02-23T02:32:35Z

BPeat at 02:27, 23 February 2019

2019-02-23T02:27:39Z

BPeat: BPeat moved page Data Flow Graph to Data Flow Graph (DFG) without leaving a redirect

2019-02-23T02:21:36Z

BPeat moved page Data Flow Graph to Data Flow Graph (DFG) without leaving a redirect

BPeat: Created page with "{{#seo: |title=PRIMO.ai |titlemode=append |keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, M..."

2019-02-23T02:21:00Z

Created page with "{{#seo: |title=PRIMO.ai |titlemode=append |keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, M..."

New page

{{#seo:
|title=PRIMO.ai
|titlemode=append
|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
}}
[http://www.youtube.com/results?search_query=Data+Flow+ Graph+Feature+deep+Visualization+~tool YouTube search...]
[http://www.google.com/search?q=Data+Flow+ Graph+Feature+Visualization+deep+machine+learning+ML ...Google search]

A data-flow graph (DFG) is a graph which represents a data dependencies between a number of operations. Any algorithm consists of a number of ordered operations.

@@ Line 5: / Line 5: @@
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[http://www.youtube.com/results?search_query=Data+Flow+Graph+DFG+deep+machine+learning+ML YouTube search...]
+[https://www.youtube.com/results?search_query=Data+Flow+Graph+DFG+deep+machine+learning+ML YouTube search...]
-[http://www.google.com/search?q=Data+Flow+Graph+DFG+deep+machine+learning+ML+artificial+intelligence ...Google search]
+[https://www.google.com/search?q=Data+Flow+Graph+DFG+deep+machine+learning+ML+artificial+intelligence ...Google search]
 * [[Visualization]]
@@ Line 12: / Line 12: @@
 * [[Directed Acyclic Graph (DAG)]]
 * [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]]
-* [http://idl.cs.washington.edu/papers/tfgraph/ Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow | K. Wongsuphasawat, D. Smilkov, J. Wexler, J. Wilson, D. Mané, D. Fritz, D. Krishnan, F. B. Viégas, & M. Wattenberg - UW Interactive Data Lab]
+* [https://idl.cs.washington.edu/papers/tfgraph/ Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow | K. Wongsuphasawat, D. Smilkov, J. Wexler, J. Wilson, D. Mané, D. Fritz, D. Krishnan, F. B. Viégas, & M. Wattenberg - UW Interactive Data Lab]
 A data-flow graph (DFG) is a graph which represents a data dependencies between a number of operations. Any algorithm consists of a number of ordered operations.
@@ Line 24: / Line 24: @@
 ** Special Edges: These edges are not data carriers between the output of a node (operator) and the input of another node. A special edge indicates a control dependency between two nodes. Let's suppose we have two nodes A and B and a special edges connecting A to B; it means that B will start its operation only when the operation in A ends. Special edges are used in Data Flow Graph to set the happens-before relationship between operations on the tensors.
-http://idl.cs.washington.edu/static/images/figures/tfgraph.png
+https://idl.cs.washington.edu/static/images/figures/tfgraph.png
-* [http://vimeo.com/237663041 Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow]
+* [https://vimeo.com/237663041 Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow]
 <youtube>NTL12U1X2fc</youtube>
 <youtube>QzF2Iii4s5c</youtube>

@@ Line 10: / Line 10: @@
 * [[Visualization]]
 * [[TensorBoard]]
 * [http://idl.cs.washington.edu/papers/tfgraph/ Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow | K. Wongsuphasawat, D. Smilkov, J. Wexler, J. Wilson, D. Mané, D. Fritz, D. Krishnan, F. B. Viégas, & M. Wattenberg - UW Interactive Data Lab]

← Older revision		Revision as of 02:51, 23 February 2019
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	[http://www.google.com/search?q=Data+Flow+Graph+DFG+deep+machine+learning+ML+artificial+intelligence ...Google search]		[http://www.google.com/search?q=Data+Flow+Graph+DFG+deep+machine+learning+ML+artificial+intelligence ...Google search]

		+	* [[Visualization]]
		+	* [[TensorBoard]]
	* [http://idl.cs.washington.edu/papers/tfgraph/ Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow \| K. Wongsuphasawat, D. Smilkov, J. Wexler, J. Wilson, D. Mané, D. Fritz, D. Krishnan, F. B. Viégas, & M. Wattenberg - UW Interactive Data Lab]		* [http://idl.cs.washington.edu/papers/tfgraph/ Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow \| K. Wongsuphasawat, D. Smilkov, J. Wexler, J. Wilson, D. Mané, D. Fritz, D. Krishnan, F. B. Viégas, & M. Wattenberg - UW Interactive Data Lab]

@@ Line 7: / Line 7: @@
 [http://www.youtube.com/results?search_query=Data+Flow+Graph+DFG+deep+machine+learning+ML YouTube search...]
 [http://www.google.com/search?q=Data+Flow+Graph+DFG+deep+machine+learning+ML+artificial+intelligence ...Google search]
 A data-flow graph (DFG) is a graph which represents a data dependencies between a number of operations. Any algorithm consists of a number of ordered operations.
@@ Line 17: / Line 19: @@
 ** Special Edges: These edges are not data carriers between the output of a node (operator) and the input of another node. A special edge indicates a control dependency between two nodes. Let's suppose we have two nodes A and B and a special edges connecting A to B; it means that B will start its operation only when the operation in A ends. Special edges are used in Data Flow Graph to set the happens-before relationship between operations on the tensors.
 <youtube>NTL12U1X2fc</youtube>
 <youtube>QzF2Iii4s5c</youtube>

← Older revision		Revision as of 02:38, 23 February 2019
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	** Special Edges: These edges are not data carriers between the output of a node (operator) and the input of another node. A special edge indicates a control dependency between two nodes. Let's suppose we have two nodes A and B and a special edges connecting A to B; it means that B will start its operation only when the operation in A ends. Special edges are used in Data Flow Graph to set the happens-before relationship between operations on the tensors.		** Special Edges: These edges are not data carriers between the output of a node (operator) and the input of another node. A special edge indicates a control dependency between two nodes. Let's suppose we have two nodes A and B and a special edges connecting A to B; it means that B will start its operation only when the operation in A ends. Special edges are used in Data Flow Graph to set the happens-before relationship between operations on the tensors.
		+
		+	<youtube>NTL12U1X2fc</youtube>
		+	<youtube>QzF2Iii4s5c</youtube>

← Older revision		Revision as of 02:27, 23 February 2019
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	A data-flow graph (DFG) is a graph which represents a data dependencies between a number of operations. Any algorithm consists of a number of ordered operations.		A data-flow graph (DFG) is a graph which represents a data dependencies between a number of operations. Any algorithm consists of a number of ordered operations.
		+
		+	* Node: In TensorFlow, each node represents the instantion of an operation. Each operation has >= inputs and >= 0 outputs.
		+
		+	* Edges: In TensorFlow, there are two types of edge:
		+
		+	** Normal Edges: They are carriers of data structures (tensors), where an output of one operation (from one node) becomes the input for another operation.
		+
		+	** Special Edges: These edges are not data carriers between the output of a node (operator) and the input of another node. A special edge indicates a control dependency between two nodes. Let's suppose we have two nodes A and B and a special edges connecting A to B; it means that B will start its operation only when the operation in A ends. Special edges are used in Data Flow Graph to set the happens-before relationship between operations on the tensors.

← Older revision	Revision as of 02:21, 23 February 2019
(No difference)