[relax][frontend][tflite] Add tests for fully_connected/depthwise_conv2d/transpose_conv/l2_pool2d#19372
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0xjah wants to merge 3 commits intoapache:mainfrom
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[relax][frontend][tflite] Add tests for fully_connected/depthwise_conv2d/transpose_conv/l2_pool2d#193720xjah wants to merge 3 commits intoapache:mainfrom
0xjah wants to merge 3 commits intoapache:mainfrom
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This pull request adds new test cases for the TFLite frontend, covering the fully_connected, depthwise_conv2d, transpose_conv, and l2_pool2d operators. It is recommended to include structural checks with expected IR modules in these tests to verify the correct lowering of operators and enhance test robustness.
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- Fix test_depthwise_conv2d: Correct kernel shape from (3,3,2,2) to (3,3,1,2)
- For depthwise convolution with 2 input channels and grouping, kernel should have shape
(height, width, input_channels_per_group, depth_multiplier) = (3, 3, 1, 2)
- This matches the format required by tf.nn.depthwise_conv2d
- Fix test_l2_pool2d: Replace deprecated tf.compat.v1.nn.l2_pool with tf.nn.pool
- tf.compat.v1.nn.l2_pool is no longer available in current TensorFlow versions
- Use tf.nn.pool with AVG pooling type and appropriate window shape and strides
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Please have a look at the CI and fix it as well :) |
Changed kernel shape from (3,3,1,2) to (3,3,2,1) because: - Input shape is (1,8,8,2) with 2 channels - depthwise_conv2d filter format: [height, width, in_channels, depth_multiplier] - With 2 input channels, third dimension must be 2 (not 1) - Using (3,3,2,1) means 2 output channels (one multiplier per input channel)
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This PR adds Relax TFLite frontend test coverage for:
Part of fixing #18971.