Hello dear team,

I’m trying to solve the “**Image_segmentation_Unet_v2**” programming task.

All previous tasks work fine. But when putting the model together (Task 3.4 - Build the Model) I get the following test error result:

Test failed

Expected value[‘Conv2D’, (None, 96, 128, 23), 759, ‘same’, ‘linear’, ‘GlorotUniform’]

does not match the input value:

[‘Conv2D’, (None, 96, 128, 32), 1056, ‘same’, ‘linear’, ‘GlorotUniform’]

AssertionError Traceback (most recent call last)

in

5

6 unet = unet_model((img_height, img_width, num_channels))

----> 7 comparator(summary(unet), outputs.unet_model_output)/tf/W3A2/test_utils.py in comparator(learner, instructor)

19 “\n\n does not match the input value: \n\n”,

20 colored(f"{a}", “red”))

—> 21 raise AssertionError(“Error in test”)

22 print(colored(“All tests passed!”, “green”))

23AssertionError: Error in test

When adding some prints for the shapes it shows the following:

encoding

cblock1[0]: Tensor(“max_pooling2d_78/MaxPool:0”, shape=(None, 48, 64, 32), dtype=float32)

cblock2[0]: Tensor(“max_pooling2d_79/MaxPool:0”, shape=(None, 24, 32, 64), dtype=float32)

cblock3[0]: Tensor(“max_pooling2d_80/MaxPool:0”, shape=(None, 12, 16, 128), dtype=float32)

cblock4[0]: Tensor(“max_pooling2d_81/MaxPool:0”, shape=(None, 6, 8, 256), dtype=float32)

cblock5[0]: Tensor(“dropout_40/cond/Identity:0”, shape=(None, 6, 8, 512), dtype=float32)

2nd index

cblock1[1]: Tensor(“conv2d_391/Relu:0”, shape=(None, 96, 128, 32), dtype=float32)

cblock2[1]: Tensor(“conv2d_393/Relu:0”, shape=(None, 48, 64, 64), dtype=float32)

cblock3[1]: Tensor(“conv2d_395/Relu:0”, shape=(None, 24, 32, 128), dtype=float32)

cblock4[1]: Tensor(“dropout_39/cond/Identity:0”, shape=(None, 12, 16, 256), dtype=float32)

cblock5[1]: Tensor(“dropout_40/cond/Identity:0”, shape=(None, 6, 8, 512), dtype=float32)

decoding

ublock6: Tensor(“conv2d_401/Relu:0”, shape=(None, 12, 16, 256), dtype=float32)

ublock7: Tensor(“conv2d_403/Relu:0”, shape=(None, 24, 32, 128), dtype=float32)

ublock8: Tensor(“conv2d_405/Relu:0”, shape=(None, 48, 64, 64), dtype=float32)

ublock9: Tensor(“conv2d_407/Relu:0”, shape=(None, 96, 128, 32), dtype=float32)

Any hints for me?

Thank you for looking into this.