C5 W1 A3 Problem with reshape in djmodel()

Course Q&A Deep Learning Specialization Sequence Models
1

Hi,

I’m trying to solve the first exercise of the 3rd assignment of week 1 in the Sequence Models course. I’m having some problems with the code. I won’t put my code as per the code of honor, but I’m getting the following error in the reshape layer:

InvalidArgumentError: Input to reshape is a tensor with 2 values, but the requested shape has 180 [Op:Reshape]

In the previous step, I have sliced X to a shape=(None, 90), and I’m passing the tuple (1, n_values) as an argument to the reshaper layer.

Can anyone guide as to where I’m going wrong?

Happy to share the code by DM if it helps.

2

Instruction says, Step 2.B: Use reshaper to reshape x to be (1, n_values) (≈1 line). It means you have to pass x which is the shape of (None, 90) as an argument to the reshaper, and then it will return the (1, n_values) shape.

1 Like
3

Brilliant, thank you! I was implementing all the layer functions wrong

4

the reshaper for actually returns x as (None,1,n_values), in my case (None,1,90). Is this right or I should have (1,n_values)

When i run the output = summary(model)

I get the following error:

AttributeError                            Traceback (most recent call last)
<ipython-input-53-2ad560a25ebc> in <module>
      2 
      3 # UNIT TEST
----> 4 output = summary(model)
      5 comparator(output, djmodel_out)

~/work/W1A3/test_utils.py in summary(model)
     34     result = []
     35     for layer in model.layers:
---> 36         descriptors = [layer.__class__.__name__, layer.output_shape, layer.count_params()]
     37         if (type(layer) == Conv2D):
     38             descriptors.append(layer.padding)

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in output_shape(self)
   2190                            'ill-defined for the layer. '
   2191                            'Use `get_output_shape_at(node_index)` '
-> 2192                            'instead.' % self.name)
   2193 
   2194   @property

AttributeError: The layer “reshape” has multiple inbound nodes, with different output shapes. Hence the notion of “output shape” is ill-defined for the layer. Use get_output_shape_at(node_index) instead.

5

I have the same output as you have. I added some print statements in my code and below are a few lines from a long loop:

Shape of x after Step 2.A: (None, 90)
Shape of x after Step 2.B: (None, 1, 90)

You can add print statement to check yours:

print(f"Shape of x after Step 2.A: {x.shape}")
# Step 2.B: Use reshaper to reshape x to be (1, n_values) (≈1 line)
x = None
print(f"Shape of x after Step 2.B: {x.shape}")
6

This error went away for me after rerunning the notebook. That is, I was seeing this error with all the code being correct.

2 Likes
7

There are lots of ways that the notebook state can get out of sync, e.g. manually running cells out of order. The way to get everything in sync is:

Kernel -> Restart and Clear Output
Save
Cell -> Run All

Of course the grader does not need to see your output, so you can submit after just the “restart and clear”, plus a “Save” just to make sure.

1 Like
8

The shape of x in my code is different, it’s (30, 90) after step 2.A and (30, 1, 90) after step 2.B, yet i get the same exact error and can’t find a solution

9

It means your code for step 2.A is not correct. In the instructions, they give example:

var1 = array1[:,1,:]

In our code, we want for t.

10

but isn’t x a 2D array ? how can i slice it as if it is 3D ?

11

Like this.