Successive STFT transforms with tensorflow increases signal amplitude - tensorflow

Question

I currently need to include STFT layers in a neural network, and I am using tensorflow's STFT.
To test it, I successively applied STFT and iSTFT transforms several time on a signal, and the amplitude of the signal grows with each transform.
The parameters I used are the following (both for STFT and iSTFT):
STFT = tf.signal.stft(np.array(sig), frame_length=174, frame_step=43, fft_length=174)
I tried librosa's STFT with the exact same parameters and this doesn't happen (the signal is the exact same after each transform). Is this normal behaviour? Am I missing something?
Edit: Here is an example of what I mean:
This is what an simple sine looks like after three consecutive STFT/iSTFT with librosa (you only see one curve because they are merged, as should be)
This is what the same curve looks like after three consecutive STFT/iSTFT with tensorflow. The original sine wave is in blue, I get the yellow curve after one STFT/iSTFT, then green, then red.
Here is the exact code:
import librosa
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
LENGTH=88
def get_STFT_librosa(sig):
fft_size = (LENGTH-1)*2
hop_size = int(fft_size/4)
spec_librosa = librosa.core.stft(np.array(sig), n_fft=(LENGTH-1)*2, hop_length=hop_size, win_length=fft_size)
return spec_librosa
def get_iSTFT_librosa(spec):
fft_size = (LENGTH-1)*2
hop_size = int(fft_size/4)
inverse = librosa.core.istft(spec, hop_length=hop_size, win_length=fft_size)
return inverse
def get_STFT_tf(sig):
STFT = tf.signal.stft(np.array(sig), frame_length=(LENGTH-1)*2, frame_step=int((LENGTH-1)*2/4), fft_length=(LENGTH-1)*2)#,
STFT = STFT.numpy()
spec_tf = STFT.T
return spec_tf
def get_iSTFT_tf(spec):
STFT = tf.convert_to_tensor(spec.T)
sig = tf.signal.inverse_stft(STFT, frame_length=(LENGTH-1)*2, frame_step=int((LENGTH-1)*2/4), fft_length=(LENGTH-1)*2)#,
return sig.numpy()
def librosa_tf_comparison():
time = np.arange(0, 1000, 0.1);
sig = np.sin(time)
#STFT level 1
tf_STFT = get_STFT_tf(sig)
lib_STFT = get_STFT_librosa(sig)
tf_iSTFT = get_iSTFT_tf(tf_STFT)
lib_iSTFT = get_iSTFT_librosa(lib_STFT)
#STFT level 2
tf_STFT2 = get_STFT_tf(tf_iSTFT)
lib_STFT2 = get_STFT_librosa(lib_iSTFT)
tf_iSTFT2 = get_iSTFT_tf(tf_STFT2)
lib_iSTFT2 = get_iSTFT_librosa(lib_STFT2)
#STFT level 3
tf_STFT3 = get_STFT_tf(tf_iSTFT2)
lib_STFT3 = get_STFT_librosa(lib_iSTFT2)
tf_iSTFT3 = get_iSTFT_tf(tf_STFT3)
lib_iSTFT3 = get_iSTFT_librosa(lib_STFT3)
plt.plot(sig[:800])
plt.plot(tf_iSTFT[:800])
plt.plot(tf_iSTFT2[:800])
plt.plot(tf_iSTFT3[:800])
plt.show()
plt.plot(sig[:800])
plt.plot(lib_iSTFT[:800])
plt.plot(lib_iSTFT2[:800])
plt.plot(lib_iSTFT3[:800])
plt.show()
librosa_tf_comparison()