I hereby claim:
- I am rachtsingh on github.
- I am rachitsingh (https://keybase.io/rachitsingh) on keybase.
- I have a public key ASAtaQuPwR-0aYEy7PkgjheFZh-b4C2ZfWG7ssWrHRDi8Qo
To claim this, I am signing this object:
Rachit Singh rachtsingh
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| Loading data from 'data/small-train.t7'... | |
| * vocabulary size: source = 50004; target = 50004 | |
| * additional features: source = 0; target = 0 | |
| * maximum sequence length: source = 50; target = 51 | |
| * number of training sentences: 100000 | |
| * maximum batch size: 64 | |
| Building model... | |
| * using input feeding | |
| Initializing parameters... | |
| * number of parameters: 84814004 |
rachtsingh
/ batch_norm.log
Last active
December 30, 2016 07:38
seq2seq with batch normalization enabled
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| Loading data from 'data/small-train.t7'... | |
| * vocabulary size: source = 50004; target = 50004 | |
| * additional features: source = 0; target = 0 | |
| * maximum sequence length: source = 50; target = 51 | |
| * number of training sentences: 100000 | |
| * maximum batch size: 64 | |
| Building model... | |
| * using input feeding | |
| Initializing parameters... | |
| * number of parameters: 84834004 |
rachtsingh
/ layer_norm.log
Created
December 30, 2016 19:38
seq2seq with layer normalization enabled
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| Loading data from 'data/small-train.t7'... | |
| * vocabulary size: source = 50004; target = 50004 | |
| * additional features: source = 0; target = 0 | |
| * maximum sequence length: source = 50; target = 51 | |
| * number of training sentences: 100000 | |
| * maximum batch size: 64 | |
| Building model... | |
| * using input feeding | |
| Initializing parameters... | |
| * number of parameters: 84818004 |
rachtsingh
/ batch_norm_no_opt.log
Created
January 1, 2017 06:22
Batch norm with no memory optimization on the nn.BatchNormalization modules
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| Loading data from 'data/small-train.t7'... | |
| * vocabulary size: source = 50004; target = 50004 | |
| * additional features: source = 0; target = 0 | |
| * maximum sequence length: source = 50; target = 51 | |
| * number of training sentences: 100000 | |
| * maximum batch size: 64 | |
| Building model... | |
| * using input feeding | |
| Initializing parameters... | |
| * number of parameters: 84834004 |
rachtsingh
/ gist:ff6c22a6dfadb41808e9586f8d905163
Created
January 30, 2017 14:09
Batch Normalization
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| [01/30/17 12:34:39 INFO] Using GPU(s): 1 | |
| [01/30/17 12:34:39 INFO] Loading data from '../data/translate-train.t7'... | |
| [01/30/17 12:34:44 INFO] * vocabulary size: source = 50004; target = 50004 | |
| [01/30/17 12:34:44 INFO] * additional features: source = 0; target = 0 | |
| [01/30/17 12:34:44 INFO] * maximum sequence length: source = 50; target = 51 | |
| [01/30/17 12:34:44 INFO] * number of training sentences: 100000 | |
| [01/30/17 12:34:44 INFO] * maximum batch size: 64 | |
| [01/30/17 12:34:44 INFO] Building model... | |
| [01/30/17 12:34:48 INFO] * using input feeding | |
| [01/30/17 12:34:48 INFO] Initializing parameters... |
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| [01/30/17 13:57:47 INFO] Using GPU(s): 1 | |
| [01/30/17 13:57:47 INFO] Loading data from '../data/translate-train.t7'... | |
| [01/30/17 13:57:51 INFO] * vocabulary size: source = 50004; target = 50004 | |
| [01/30/17 13:57:51 INFO] * additional features: source = 0; target = 0 | |
| [01/30/17 13:57:51 INFO] * maximum sequence length: source = 50; target = 51 | |
| [01/30/17 13:57:51 INFO] * number of training sentences: 100000 | |
| [01/30/17 13:57:51 INFO] * maximum batch size: 64 | |
| [01/30/17 13:57:51 INFO] Building model... | |
| [01/30/17 13:57:55 INFO] * using input feeding | |
| [01/30/17 13:57:56 INFO] Initializing parameters... |
rachtsingh
/ keybase.md
Created
May 27, 2017 04:15
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| #include "ATen/NativeFunctions.h" | |
| #include "ATen/Dispatch.h" | |
| #include "ATen/cuda/CUDAApplyUtils.cuh" | |
| #include <curand.h> | |
| #include <curand_kernel.h> | |
| #include <curand_philox4x32_x.h> | |
| #include <utility> | |
| #include <functional> | |
| #include <nvfunctional> |
rachtsingh
/ number_of_samples.py
Last active
April 24, 2018 18:22
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| import numpy as np | |
| from matplotlib import pyplot as plt | |
| def sample_gamma(alpha): | |
| total = 0 | |
| scale = 1. | |
| if (alpha < 1.0): | |
| scale *= (1 - np.random.uniform() ** (1.0 / alpha)) | |
| total += 1 |
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| #include <stdio.h> | |
| // void * return type means that it returns a naked pointer, which is just an address. | |
| void *foo(void) { | |
| long bar = 5; | |
| printf("bar's address is: %p, holds %ld bytes\n", &bar, sizeof(long)); | |
| long *ret = &bar; | |
| return (void *) ret; // ret is a pointer to a long, but we just turn it into a regular address | |
| // note that the previous line doesn't *do* anything, it just gets the compiler off our back | |
| } |