Add SqueezeNet Fire Module #585
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syed-nazmus-sakib wants to merge 2 commits intoOpen-Deep-ML:mainfrom
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moe18
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Mar 5, 2026
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looks good, had a few ideas for the test cases
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| { | |||
| "input": "imput_tensor: (H=32, W=32, C_in=3)\nSqueeze 1x1: s1x1=16 filters\nExpand 1x1: e1x1=64 filters\nExpand 3x3: e3x3=64 filters", | |||
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should be input_tensor (small spelling issue)
| { | ||
| "test": "import numpy as np\n# Middle pixel full sum\n# Same setup as above, check middle pixel (1,1)\n# 9 neighbors are 1s -> Sum = 9\ninput = np.ones((3, 3, 1))\ns_w = np.ones((1, 1, 1, 1))\ns_b = np.zeros(1)\ne1_w = np.zeros((1, 1, 1, 1))\ne1_b = np.zeros(1)\ne3_w = np.ones((3, 3, 1, 1))\ne3_b = np.zeros(1)\nres = fire_module_forward(input, s_w, s_b, e1_w, e1_b, e3_w, e3_b)\nprint(res[1, 1, 1])", | ||
| "expected_output": "9.0" | ||
| } |
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add a test for Non-Zero Bias
| }, | ||
| { | ||
| "test": "import numpy as np\n# Middle pixel full sum\n# Same setup as above, check middle pixel (1,1)\n# 9 neighbors are 1s -> Sum = 9\ninput = np.ones((3, 3, 1))\ns_w = np.ones((1, 1, 1, 1))\ns_b = np.zeros(1)\ne1_w = np.zeros((1, 1, 1, 1))\ne1_b = np.zeros(1)\ne3_w = np.ones((3, 3, 1, 1))\ne3_b = np.zeros(1)\nres = fire_module_forward(input, s_w, s_b, e1_w, e1_b, e3_w, e3_b)\nprint(res[1, 1, 1])", | ||
| "expected_output": "9.0" |
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ReLU Is Never Actually Tested in any of the test cases
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Thanks for the review! I've pushed the updates. imput_tensor is now input_tensor, and I've added non-zero bias and ReLU edge-case tests to test.json file.
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Description
This PR implements Problem 190: SqueezeNet Fire Module, which teaches how to use 1x1 convolutions ("squeeze" layer) to reduce dimensionality before applying expensive 3x3 convolutions ("expand" layer).
Changes
questions/190_implement-squeezenet-fire-module/with all required files.meta.json,description.md,learn.md,starter_code.py,solution.py,example.json, andtests.json.utils/build_bundle.pyfix for Windows encoding to ensure this branch passes CI independently.utils/validate_questions.py.Checklist