From 652ca8e003ef0341dba4e6823955d63163b3f668 Mon Sep 17 00:00:00 2001 From: Saad Khan <38633812+saadulkh@users.noreply.github.com> Date: Thu, 30 Nov 2023 17:13:56 +0500 Subject: [PATCH] Fix (brevitas_examples/bnn_pynq): fix for no cuda error * code: Fixed `gpus` default to `None` * readme: Fixed train and eval commands --- src/brevitas_examples/bnn_pynq/README.md | 6 +++--- src/brevitas_examples/bnn_pynq/bnn_pynq_train.py | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/src/brevitas_examples/bnn_pynq/README.md b/src/brevitas_examples/bnn_pynq/README.md index 6e1c52727..f27300345 100644 --- a/src/brevitas_examples/bnn_pynq/README.md +++ b/src/brevitas_examples/bnn_pynq/README.md @@ -31,17 +31,17 @@ A few notes on training: To start training a model from scratch, e.g. LFC_1W1A, run: ```bash -BREVITAS_JIT=1 brevitas_bnn_pynq_train --network LFC_1W1A --experiments /path/to/experiments +BREVITAS_JIT=1 python bnn_pynq_train.py --network LFC_1W1A --experiments /path/to/experiments ``` ## Evaluate To evaluate a pretrained model, e.g. LFC_1W1A, run: ```bash -BREVITAS_JIT=1 brevitas_bnn_pynq_train --evaluate --network LFC_1W1A --pretrained +BREVITAS_JIT=1 python bnn_pynq_train.py --evaluate --network LFC_1W1A --pretrained ``` To evaluate your own checkpoint, of e.g. LFC_1W1A, run: ```bash -BREVITAS_JIT=1 brevitas_bnn_pynq_train --evaluate --network LFC_1W1A --resume /path/to/checkpoint.tar +BREVITAS_JIT=1 python bnn_pynq_train.py --evaluate --network LFC_1W1A --resume /path/to/checkpoint.tar ``` diff --git a/src/brevitas_examples/bnn_pynq/bnn_pynq_train.py b/src/brevitas_examples/bnn_pynq/bnn_pynq_train.py index fd4281a3c..5aa316aea 100644 --- a/src/brevitas_examples/bnn_pynq/bnn_pynq_train.py +++ b/src/brevitas_examples/bnn_pynq/bnn_pynq_train.py @@ -52,7 +52,7 @@ def parse_args(args): add_bool_arg(parser, "detect_nan", default=False) # Compute resources parser.add_argument("--num_workers", default=4, type=int, help="Number of workers") - parser.add_argument("--gpus", type=none_or_str, default="0", help="Comma separated GPUs") + parser.add_argument("--gpus", type=none_or_str, default=None, help="Comma separated GPUs") # Optimizer hyperparams parser.add_argument("--batch_size", default=100, type=int, help="batch size") parser.add_argument("--lr", default=0.02, type=float, help="Learning rate")