import streamlit as st

def number_field(label, **args):
  c1, c2 = st.columns([2, 4])
  c1.write(label)
  
  return c2.number_input('', **args)

st.header("Transformer parameters")
col1, col2 = st.columns([2, 4])

bs = number_field('Batch size', value=10)
h = number_field('Num heads', value=16)
d = number_field('Dimension', value=768)
n = number_field('Seq length', value=1024)

st.header('Query, Key, Value projection')

mha_flop = 2*bs*n*d*3*d
mha_bytes = 2*bs*n*d + 2*3*d*d + 2*bs*n*3*d

st.subheader("Multi-query Attention")
c1, c2 = st.columns([2, 3])
c1.write("FLOP:")
c2.write(str(mha_flop))
c1.write("Bytes: ")
c2.write(str(mha_bytes))
c1.write("Arithm. intensity:")
c2.write(str(mha_flop/mha_bytes))

mqa_flop = 2*bs*n*d*(1+2/h)*d
mqa_bytes = 2*bs*n*d + 2*(2/h)*d*d + 2*bs*n*(2/h)*d

st.subheader("Multi-query Attention")
c1, c2 = st.columns([2, 3])
c1.write("FLOP:")
c2.write(str(mqa_flop))
c1.write("Bytes: ")
c2.write(str(mqa_bytes))
c1.write("Arithm. intensity:")
c2.write(str(mqa_flop/mqa_bytes))

st.header('Attention')