def _test_tflite2_quantized_depthwise_convolution(input_shape, kernel_shape,
dilations, strides, padding, data_format, depth_multiplier):
"""One iteration of TFLite2 quantized depthwise convolution with given shapes and attributes"""
+
data_format = "channels_last" if "NHWC" else "channels_first"
data = np.random.uniform(0, 1, input_shape).astype('float32')
kernel = np.random.uniform(0, 1, kernel_shape).astype('float32')
_test_tflite2_quantized_convolution([1, 17, 17, 19], [3, 3, 19, 19], [1, 1], [2, 2], 'VALID', 'NHWC')
_test_tflite2_quantized_convolution([1, 17, 17, 124], [1, 1, 124, 19], [1, 1], [1, 1], 'SAME', 'NHWC')
+ # Disable as tests are flaky - https://github.com/apache/incubator-tvm/issues/6064
# depthwise convolution
- _test_tflite2_quantized_depthwise_convolution([1, 8, 8, 128], [1, 1, 128, 1], [1, 1], [1, 1],
- 'SAME', 'NHWC', 1)
- _test_tflite2_quantized_depthwise_convolution([1, 17, 17, 12], [3, 3, 12, 1], [1, 1], [2, 2],
- 'VALID', 'NHWC', 1)
- _test_tflite2_quantized_depthwise_convolution([1, 24, 24, 3], [7, 7, 3, 8], [1, 1], [2, 2],
- 'SAME', 'NHWC', 8)
+ # _test_tflite2_quantized_depthwise_convolution([1, 8, 8, 128], [1, 1, 128, 1], [1, 1], [1, 1],
+ # 'SAME', 'NHWC', 1)
+ # _test_tflite2_quantized_depthwise_convolution([1, 17, 17, 12], [3, 3, 12, 1], [1, 1], [2, 2],
+ # 'VALID', 'NHWC', 1)
+ # _test_tflite2_quantized_depthwise_convolution([1, 24, 24, 3], [7, 7, 3, 8], [1, 1], [2, 2],
+ # 'SAME', 'NHWC', 8)